Machine Gun Kelly takes the wheel in gripping crime drama One Way – Boston Herald

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MOVIE REVIEW

ONE WAY

Rated R. On VOD.

Grade B+

Gripping and clever, although not entirely, One Way tells the story of a fugitive on the run, or I should say, on a bus, trying to get away from a gang from which he has stolen cash and cocaine.

When this crime drama starts, Freddy (Colson Baker aka Machine Gun Kelly) and his two partners have already stolen the goods from Freddys lover and gang leader Vic (Drea De Matteo, The Sopranos). One of Freddys cohorts is already captured and is about to be killed. Another, a guy named JJ (Luis Da Silva Jr.), is in a car on the road following the bus and terrified. Freddy has a gun, the cash and coke. But he has been shot in the stomach, and hes bleeding out.

Also on the bus is the no-nonsense driver (the talented Thomas Francis Murphy); an underage girl named Rachel (Storm Reid, TVs Euphoria) texting with a man shes supposed to meet named Smokie; a pregnant woman on her own; and a social worker named Will (Travis Fimmel). Also in the mix are Freddys estranged, criminal father Fred Sr. (Kevin Bacon), Freddys estranged ex-wife Christine (Meagan Holder), who is a nurse, and Freddy and Christines daughter Lily (Casie Baker, who is MGKs real-life daughter).

In addition to its almost Shakespearean family ties (Freddys father was also Vics lover, making Freddys connection borderline incestuous), One Way pumps a hefty weight of metaphor, The bus ride is a symbol of Freddys life. How long before it might end at the Cairo, Ga., bus station? People get on and get off. A ghostly figure appears to a hallucinating Freddy. Is he the Banquo of One Way?

Directed by Irishman and Roger Corman school of filmmaking graduate Andrew Baird and written by Irishman Ben Conway, both making their feature film debuts (Baird has another film awaiting release), One Way is steeped in morbid nihilism. Freddy cannot stop the bleeding. But that doesnt stop him from getting to know Rachel after she asks to borrow one of his phones. She notices that he has two and assumes he is a gang banger. Will suspiciously intervenes to make sure Freddy isnt trying to take advantage of the girl. The pregnant woman spies on the others. The bus driver might be a Southern-fried Charon ferrying his passengers to the underworld.

With his nose ring and bleached locks, Freddy might be a rock star. Freddy has a desperate plan to get JJ to drive him to a vet to get stitched up. Later, he plans to meet Christine in a parking lot and let her do it. In desperation, Freddy takes a few heavy snorts of coke.

In many ways, One Way is a modern-day re-imagining of the masterful Carol Reed thriller Odd Man Out (1947) with James Mason as a wounded Belfast gunman on the run from the police and increasingly cornered. Both films have a powerful nightmarish element.

Baker, who has played leads twice before, is not yet a great actor. But he is a reasonably good one, and he has charisma and screen presence. In one of the films more Shakespearean twists, Freddy has a rare blood type and needs his father to donate his blood to survive.

As you might expect for a movie starring a musician, the music by British composer Raffertie (I May Destroy You) is a strong element. Also noteworthy are singles by Zachary Stephen Selwyn, including the suitably titled tune New Suit for My Hangin.

One Way contains violence, profanity and mature themes.

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Machine Gun Kelly takes the wheel in gripping crime drama One Way - Boston Herald

When Kanye threw shade on ‘that gang in Philly’ he was probably coming for Penn – Billy Penn

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It was only a matter of time before Philadelphia found itself in the middle of some Kanye West beef.

The rapper-slash-entrepreneur-slash-infamous-shitposter on Thursday morning called out Adidas GM Daniel Cherry III in a now-deleted Instagram post. Im a nice person but Im starting to feel like not being nice, West wrote under a screenshot of Cherry from an article on comic book news website Bleeding Cool. And dont try to tell me what gang you used to role [sic] with in Philly this time.

The post, obviously, sent the internet into a spiral of confusion.

Who was Daniel Cherry III and what had he done to make West mad? Was he, in fact, gang-affiliated? And, as frequent Kanye collaborator Pusha T. wrote in a comment, are there even gangs in Philly?

Our take: This disagreement has nothing to do with gang affiliation and everything to do with the University of Pennsylvania and a failed business deal.

When Cherry lived in Philly during the 1990s, he wasnt in a gang. He was a student at Penn, where he majored in Africana and Urban Studies. During his time at the Ivy League university, Cherry was involved with the Black Student League and the Greenfield Intercultural Center, which works with students to create programming around cross-cultural understanding.

Cherry was a thoughtful, very kind, and very generous guy just an all-around engaged Penn student, his college roommate told Billy Penn over the phone, speaking on condition of anonymity (likely for fear of Kanyes wrath). He was not in a gang by any affiliation.

The Adidas head honcho recently opened up about his experience at Penn in a lengthy Linkedin post, where he reflected on what it meant for his oldest daughter to attend lacrosse and tennis camps on the Philadelphia campus.

[Visiting Penn] brought back a flood of memories for me, Cherry wrote. I had to leave my family, my friends, the only support system I had, and the entire world I knew in order to achieve my personal ambition in life which was at the time simply to escape poverty and a small-towns oppressive racism and nihilism.

So, why is West deciding to blow up this Penn grads spot? Because business is personal.

The former director of advertising for the mythic Philly-bred brand AND1, Cherry has made a career out of working at the nexus of entertainment, apparel, and sports culture.

When Cherry left his post as general manager at DC Comics after only 16 months, rumor had it he was headed to work with West on a new, unspecified venture. That obviously didnt pan out. Cherry hopped straight from DC Comics to his current role at Adidas.

Now here we are, watching West drag Phillys name through the mud just for the sake of a viral clapback.

The rapper continued to throw jabs at Cherry for the rest of Thursday afternoon. One post reads, If you not [sic] looking to work at Yeezy full time, Dont text me or nobody I know. Were not looking for help. Our personal favorite? The How to create an angry ye starter pack, which insinuates that Adidas has been copying Wests designs.

West himself is no stranger to the University of Pennsylvania. His cousin Devo Harris, the former co-founder of Kanyes G.O.O.D music label, attended the Wharton School of Business while John Legend was studying English, and the two roomed together before Harris introduced Legend to West.

When West referenced that gang you used to [roll] with in Philly, perhaps he was referring to the small subsection of Penn alums with street cred.

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When Kanye threw shade on 'that gang in Philly' he was probably coming for Penn - Billy Penn

Humanity Is Doing Its Best Impression of a Black Hole – WIRED

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The one thing that all human civilizations have in common is that they end. For 10,000 years or so, that's been the common factor.

You can make an argument that civilizations tend not to last very long once they get to a certain level of tech. When they get to the point where they would be able to send probes out across the galaxy, or communicate at the speed of light, they don't last long in that stage. You've made a lot of technological advances, and with something like nuclear weapons or climate change, you start to be able to impact a planet as a whole. And once you get there, bad things start to happen.

With nuclear weapons, we could literally wipe ourselves out. And with the climate, anywhere close to the worst-case scenarios, if we keep going the way we're going, civilization will collapse. Large parts of the Earth will be unlivable. There are people around now who are going to experience a very different Earth. If they're still alive, which in the nuclear case, they probably won't be.

The entropy of the universe means that it gets increasingly disordered over long spans of time. But for civilization on Earth, this is not so much entropy as it is just collapse.

It's not a slow process. Entropy does its thingit wins in the end. But the time scales that are relevant for these processes, the physical time scales are very long. And what we're talking about here is very short.

For nuclear, at this moment, if someoneBiden or Putinjust decides theyve had enough, one person, one person decides, that's it. They can push a button. The way everything is structured, there's no way to countermand that, and it's done. In 30 minutes, we're all done. One person. What kind of civilization sets that up, so one person can wipe out everyone and take the entire planet down? Everything, all living things, everything. That's a little different from just entropy and historical progression.

I'm not trying to be depressing. It's a beautiful day here in Chicago. It's just very easy to get despondent. And then you go and you work on black holes, and it's uplifting in a very strange way. They're beautiful. As is the fact that we as a species can sit here and contemplate the age of the universe.

There seems to be a kind of creeping nihilism, because there's so much that's out of our control as individuals. Ive tried to spin my own version as a constructive nihilism. I am very down about our planetary happenings. But in thinking about the larger universe, there is, I think, a certain beauty in realizing our insignificance. I think the trouble there is the temptation to give upyou get complacent.

I know exactly what you're talking about, because I definitely do the same thing. It's so easy to get despondent. I do have this solace that it just doesn't matter. It's almost like I don't need to take it so personally. The universe is going to be fine.

But the planet really needs people to be engagedthat's clear. And it's not going to happen from enlightened politicians, unless everyone starts pushing for it. We do need enlightened politicians, we need enlightened corporate leaders. But we also need an enlightened citizenry that just says: Enough is enough. We can see what's happening to the planet now. It's what the scientists said would happenand they're telling us it's just going to get worse. This is not OK.

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Humanity Is Doing Its Best Impression of a Black Hole - WIRED

Joe Lycett trolls Liz Truss again after becoming next PM: ‘Smashed it babe’ – PinkNews

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Joe Lycett sarcastically congratualted Liz Truss for the win. (Getty)

Joe Lycett has continued his satirical reign of terror after Liz Truss was confirmed as Britains next prime minister.

Lycett made the front page of the Daily Mail on Monday morning (5 September), hours before Truss was confirmed as the new Tory leader and incoming PM, over his sarcastic appearance on the BBCs Sunday with Laura Kuenssberg.

After Truss was interviewed by Kuenssberg, Lycett left the host stunned by insisting that while left-wing voices might dismiss Truss as the backwash of the available [Tory] MPs, he would never say that because he is incredibly right-wing.

He continued his bit afterTruss win was announced, excitedly congratulating her in a tweet so tongue-in-cheek he could have poked a hole through his lip.

Yes [Liz Truss] absolutely smashed it babe! he wrote, and fans revelledin the passive-aggression.

Some users took the chance to lambast the newly-appointed Conservative leaders victory speech, in which she promised voting members that we will deliver, we will deliver, we will deliver, and we will deliver a great victory for the Conservative Party in 2024.

Im feeling like she will deliver, one user wrote. Maybe deliver some more and then deliver after that. Not sure what shes delivering. But Im guessing it will be like when a Royal Mail person pops a red card in the door, yet hasnt actually knocked.

While many gleefully played along with Joe Lycetts hilarious concept of being a Liz Truss supporter, the nihilism of having a Conservative leader who has failed to produce any plans on the cost of living crisis and has denied trans women are womenseemed too overwhelming to fake.

Smashed what? The economy? Workers rights? Hope? Our futures? one user said, while another added: And now shes going to smash the country. Yay.

It comes after Joe Lycetts jabs at the Conservative party during a guest spot on Sunday with Laura Kuenssberg.

After Truss gave her only interview of the leadership race to Kuenssberg, Lycett was heard cheering on the soon-to-be prime minister.

He later explained, with an air of irony so thick you could barely see the coy grin forming on his face:I know theres been criticism in theThe Mail on Sunday today about leftie liberal wokie comedians on the BBC.Im actually very right wing and I love it. I thought she gave great clear answers. I know exactly what shes up to.

After the Mail dedicated its front page to criticising his appearance on the show, Lycett responded in a tweet, saying: Ill be off to the framers in the morning.

Since then, right-wing outrage has been in full force over Lycetts jokes. Daily Express political editor Sam Lister reportedly wrote an enraged piece calling out the British comedian for the television spot, calling him a loose cannon comedian.

Meanwhile, GB News commentator Darren Grimes tweeted his own outrage, saying: The BBC offered us the opinions of comedian Joe Lycett and Emily Thornberry for the launch of their flagship political programme this morning. Riiiiiiiiight.

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Joe Lycett trolls Liz Truss again after becoming next PM: 'Smashed it babe' - PinkNews

PERSPECTIVE: Projected Hate: Gender Identity, Sexual Orientation, and …

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It is no secret that white supremacist groups are racist, antisemitic, Islamophobic, and xenophobic. They are also violently homophobic and transphobic. Indeed, sexual orientation and gender identity is the third most common hate crime motivation, behind race, ethnicity, and nationality and religion, with 171 hate crime offenders being motivated by transphobia or homophobia since 1990. This trend is unsurprising when one considers that white supremacists are often conservative Christians who condemn anything but binary sexual identities and extol traditional sex roles for men and women. Additionally, one of the most famous white supremacist slogans, We must secure the existence of our people and a future for white children, implies a requirement for heterosexual sex for the purpose of procreation and, in the eyes of white supremacists, strict gender binaries wherein women are responsible for producing and raising the future generations. White supremacists also tend to portray gay men and transgender women, in particular, as being predators who groom children for pedophilia. Therefore, white supremacists ire is directed at the LGBTQ+ community in general and specifically white people within it who are viewed as sexually perverted, a danger to their children, and as failing to do their duty to the race (i.e., maintaining traditional family values and procreating). Of course, all of these hateful ideas are incorporated into these groups overarching ideology which directs most of its hate toward Jews, positing that when Jews are not conducting the great replacement through immigration and interracial marriage, they are doing so by perverting culture and promoting homosexuality and gender fluidity. According to some white supremacist ideologies, turning white men gay also makes them easier to control.

It may be surprising, then, for the outside observer to learn that many far-right violent extremist groups advocate for LGBTQ+ rights and even have openly LGBTQ+ leaders or have embraced certain public faces identifying with the LGBTQ+ community. For example, Milo Yiannopoulos, who has decried feminazis as breaking down (white) male hegemony, is gay and claims Jewish ancestry as well. Indeed, doing so allows these violent groups to mainstream their racist claims and at the same time degrade and demonize cultures they view as backward, namely Islam. Similarly, whereas white supremacist groups typically view women as breeders who should be valued only as wives and mothers, many far-right, ultra-nationalist groups are led by women who feel empowered, albeit often because they feel as though they are exceptional and special in being respected by otherwise misogynistic men. Notably, ISIS, too, engaged in strict enforcement of traditional gender roles as a means of subjugating women while making them feel empowered in their decision to adhere to the strictest interpretation of their religion.

Whether they must hide their true identities for fear of harassment or outright assault, or have their identities exploited for the purpose of degrading and dehumanizing others, there seems to be strong reason for members of the LGBTQ community to steer clear of white supremacism and the alt-right. Yet their participation is not uncommon, particularly among white, cisgender gay men who are perceived as substandard allies, provided they are deemed to be sufficiently masculine and reject all aspects of gay culture, including having a family. Indeed, an unattached gay white man can be seen as having no familial responsibilities and thus having more time and energy to devote to the white supremacist cause. They are even more valuable to these groups if they are antifeminist and willing to verbally abuse women.

The question remains, then, as to why someone who identifies as LGBTQ+ would participate in such a group or movement, if doing so would require them to either hide their identity (to remain in the closet) or to use their identity to hurt others, including to hurt other LGBTQ+ people. Our research using in-depth psychological interviews with 51 current and former members of far-right, white supremacist, and hate groups, five of whom identified as being part of the LGBTQ+ community, participating in white supremacism may be a defense mechanism against negative thoughts about oneself internalized homophobia and transphobia arising out of cultural or familial norms that are intolerant of such identities. We refer to this process as Projected Hate, in which one who has been raised in a family, religious group, or society which rejects LGBTQ+ identities deals with the anxiety caused by being a member of this community by partially or in totality hiding this aspect of their identity and joining a homophobic or transphobic violent extremist group as part of an effort to disavow and split off an unwanted part of ones own identity. The individual subsequently projects that self-hatred onto others holding the LGBTQ+ identity and may even try to destroy them, thereby symbolically vanquishing the hated or disavowed part of the self. A slightly lesser splitting and projection process can also occur in which members of the LGBTQ+ community join such groups and split off part of their self in a less radical way but then use their sexual or gender identity as a weapon in a violent extremist group as a mechanism for building self-esteem and distinguishing oneself as unlike other members of the LGBTQ community whom they vilify. In this case, they are often trying to be the exception that is embraced by the group while hating others from the same community.

Scott E., aged 42, describes themselves as a latch-key kid. Scott recalls of childhood, It was a happy family, but we were not the most loving family in the world. [The] type of family [where] whenever things happen, [its] a suck it up, buttercup type of situation. My dad was a bit abusive when I was a kid. Not extremely. Scott says that the abuse got better as [the] years went, although perhaps this was more due to their being able to defend themselves (I was 15 [and] ended up choking him on the floor to defend myself) than due to his father realizing his wrongdoings. Prior to getting into white nationalism, however, Scott hung out with a number of men along the gender and sexual spectrum, but I realized I wasnt into men. I really dont like masculinity. Later, Scott became highly engaged on the white supremacist web forum Stormfront, where I had to hide some things. Scotts involvement on Stormfront began with the band Prussian Blue, which featured two young girls as singers, who were managed by their mother, April Gaede. Scott saw online that a man claiming to be part of Antifa wanted Black guys to go to April Gaedes house and rape these 11- and 12-year-old girls, because their mother was a white nationalist. He included a map to their house. I contacted the feds. They didnt take it seriously; said they were aware. They told me to make the parents aware of it. I contacted them, told them who I was. I wasnt worldly when it came to white nationalism, and I became a friend of the family. They even made me a moderator on the Prussian Blue forum. Later on, Scott moved to Montana where the Gaede family lived and became involved with Aprils organization, a whites-only community called Pioneer Little Europe [PLE]. Scotts belief in white nationalism ebbed and flowed. Scotts job was to make the PLE ideology more palatable, including by saying that white gay men could be white nationalists. Scott reflects back, I was worse than a Hitler lover [] because I made it more acceptable to be horrible, and thats arguably worse. I was in it for the community [] My mindset was never fully in it. I was trying to make white nationalism what I wanted it to be.

Phoebe Rose was also physically and emotionally abused by her father. Growing up in the body of a boy, Phoebe Rose says her father never understood me. I never fit the narrative he wanted. He couldnt handle me knowing more than him, any defiance, any individuality, not what he expected. Phoebe began a social transition at age 15 but felt misunderstood by doctors, leading her to attempt a male-presenting lifestyle at university and later in the British Army. The psychological strife of remaining closeted as a trans woman contributed to a mental health breakdown, after which she was honorable discharged for medical reasons. Further mental health challenges developed after being raped by a trans woman who had already surgically transitioned. At age 26, Phoebe traveled to Thailand for gender-affirming surgery. She recalls, This trip to Thailand changed my life in more ways than I can imagine. I met an American girl with a very troubled background. She was the most intelligent person I have ever encountered in my life. She started to radicalize me to the extreme right. At the time, Phoebe had been working in an organization in England which served asylum seekers, where she began to harbor Islamophobic thoughts about Albanian Muslim men trying to take the piss out of the system. Afghanis came to the UK to be pedophiles, lying about their age, saying they were children when they werent [] We would see schoolgirls going into this 40-year-olds place. Social services would do an age assessment and say he was 17. Afghanis are fanatics.

Phoebe met white nationalists online and, surprisingly enough, for the first time I found someone interested in me for just being me. [They] didnt give a toss that I [had converted to become] Jewish, that I was trans, that I was in a same-sex relationship. From there, Phoebe was connected with the English Defence League, which wanted what I wanted, Muslims out of Britain. Phoebe admits adopting a zealous, if not extremist, form of Zionism: EDL wanted England for the English. I wanted Israel for the Jews. Who is in the way? Dirty, stinking Muslims. Phoebe Rose became a prominent speaker for the EDL: I got a thrill out of it, I got a rush. Someone gave me a microphone and gave me the stage. I had them in the palm of my hand. I wasnt afraid. I didnt need a script. I knew what I was going to say, how to get them going. By the end of it, they were all standing and cheering, they had come to listen to people, but I dont think they expected a 20-something Jewish, white trans girl to steal it. Later on, she felt even more powerful: The police were scared of me because of who I am. They didnt want to arrest a Jewish woman, a trans woman. Police arrest a Jewish woman at an EDL rally, [theyd] get laughed at, what, are you stupid? That was lovely. They were scared of me. The police, the people Im supposed to be scared of, are scared of me. They have a file on me. I requested it but most is blacked out. Police officers were assigned to just me.

Viktoria, whose mother was in the U.S. Air Force but moved to East Germany after becoming pregnant, grew up in not a happy family. [My] biological father was never in the picture. Another gentleman stepped in. [He was a] pedophile and violent felon. He tried to kill my mother and me several times. We were in the hospital several times due to beatings. He used blunt objects. He signed the birth certificate. I think my mother had slept with a random man at a bar [and] I was conceived. [The] abusive guy stepped in and signed the birth certificate. My mother refused to speak about it. When I investigated, all I can learn is my [step]father is a German nationalist and terrorist. The trauma from her early childhood continued in West Virginia, where her uncle was in a militia. He trained all the kids how to kill people. We would name the hunted animals names of people we didnt like. Hed call them enemies, race traitors. We would hunt and visualize killing them. He was psychologically preparing us for murder. Over time, Viktoria developed a deep and violent commitment to white supremacism, but says that piece by piece over time, there were significant things. I saw how people saw me. I had a girlfriend younger than me. She grew up in an extremely peaceful, sheltered household, saw pieces of things I did, the way she responded. I hadnt seen that because I was surrounded by like-minded people, so unbelievably shattered just by the tip of the iceberg, how far I had gone. My sexuality, gender, queerness interfered as well. I had always known I was queer. I thought I was degenerate. I went to conversion therapy. When Viktoria came out to her family, they sent me death threats and pipe bombs. Viktoria reflects on her experience and highlights what Phoebe and Scott may have experienced in their own groups: I was not queer in the movement. Thats a death sentence. Modern groups will accept [queer people] on the outside, [but] never will make it to the inside. Useful idiots, they throw them away later, no regard for their wellbeing. Being queer in the movement is impossible. Its like being required to work in a factory and cutting off both of your arms, always this inner monologue in the back of your mind that wont stop. I tried every conversion therapy, even electroshock. [It] just builds an unbearable amount of shame. Now, she says, For self-love, coming out as queer was the best thing I ever did.

Finally, Jason V. spoke about his experience being openly queer while employed by the Oath Keepers as their national spokesperson. Jason explains that he was initially interested in the Oath Keepers when he perceived them as being libertarian, as he was, but became disillusioned with the group when they started courting the alt-right, [Richard] Spencer, the actual Nazis, Proud Boys, I just couldnt do it. Stewart Rhodes, the leader of the Oath Keepers who hired Jason, knew that he was queer and generally accepted it, though he made clear that Jason, alongside another gay couple providing support to the group, needed to hide their sexual identities from the people whom Jason was reaching and radicalizing through his propaganda. For instance, when covering the Oath Keepers support for Kim Davis, the Kentucky county clerk who refused to issue marriage licenses to same-sex couples, I wrote it from the perspective of the queer person, [saying] we need to protect same-sex growers growing pot. That was rejected by Stewart. He rewrote it. Jason cynically explains how Alex Jones, the InfoWars conspiracy theorist, made millions selling snake oil and Stewart caters his messaging to where he feels hes going to make the most money and you know, the county clerk obviously was resounding with an anti-queer sentiment within the membership and paying donors. Thus, in contrast to Phoebe and Scotts groups, which exploited members of the LGBTQ+ community in order to mainstream their ideologies, Jasons group, whose core leadership did in fact accept his identity, forced him to hide it in order to appeal to paying donors.

As can be observed from the stories in this article, growing up in an environment which makes one feel as though they do not fit into the expected, traditional gender norms can cause a great deal of emotional strain. The process of Projected Hate can be observed to different extents among the five short case studies described above. Most hid their sexual identity from their groups, knowing that it was viewed as degenerate and an anathema to the groups, unless it could be used by them. Some, like Viktoria, were actively steeped in self-hatred and shame over being gay and tried to vanquish it in themselves while going along with groups that openly and violently targeted the community of which they were a part. Most split off or at least did not publicly acknowledge their LGBTQ+ identity while in the group and supported a group that attacked and even wished to kill LGBTQ members. We saw the same occurring in ISIS, perhaps the most famous case being Omar Mateen, who came from an Afghan background and may have disavowed his homosexuality but then projected his hatred of this community by going to the same nightclub in Orlando he was known to have frequented to kill members of the LGBTQ+ community.

These case studies yield implications for practitioners working to prevent, counter, and intervene in violent extremism. Most importantly, practitioners must understand that hatred toward others can often arise as a defense against self-hatred, which arises particularly in LGBTQ+ individuals who were raised with complete intolerance of this identity. As is clear from the interviewees quoted, learning self-love can also be a pivotal step in turning away from hate groups and movements.

The views expressed here are the writers and are not necessarily endorsed by Homeland Security Today, which welcomes a broad range of viewpoints in support of securing our homeland. To submit a piece for consideration, email Editor@Hstoday.us.

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PERSPECTIVE: Projected Hate: Gender Identity, Sexual Orientation, and ...

Tracking the Foot Soldiers of White Supremacy – San Diego Jewish World

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By Eric George Tauber

CINCINNATI, Ohio Five years ago, on August 11, 2017, in the normally quiet college town of Charlottesville, VA, the peace was disrupted by the Unite the Right rally. The rally brought together Neo-Confederates, Neo-Nazis, the Klan, Patriot Front and other militias espousing White Supremacism. I dont think any of us will ever forget how we felt as we watched a mob of angry, violent men marching through the streets chanting JEWS WILL NOT REPLACE US!

That evening, congregants at Beth Israel in Charlottesville were hastily ushered out a back door carrying the Torah scrolls. Thankfully, no violence or vandalism came to the shul, but the precautions were well taken.

The rally also brought together a group of counter-demonstrators who would not let such hateful, bigoted rhetoric go unanswered. Things came to a head when a domestic terrorist, James Fields used his car as a deadly weapon by driving it into the crowd, injuring nineteen and murdering one, a lovely, bright-eyed, idealistic young woman named Heather Heyer.

The next day, the 45th occupant of the Oval Office, mindful of who his most ardent supporters are, said that there were very fine people on both sides.

On August 14, 2017, when a rabbi was a no-show at the hastily organized Unity Vigil, I proudly represented the Jewish community by singing Haveinu Shalom Aleichem.

On the fifth anniversary of this infamous rally, The United States Holocaust Memorial Museum hosted an online seminar called The Foot Soldiers of White Supremacy. Museum Historian, Dr. Rebecca Erbelding was joined by a fellow historian, Dr. Edna Friedberg and David Mills, a lawyer who sued the groups for the damage and loss of life that they caused.

What were the Alt-Right marchers trying to accomplish?

Ostensibly, they were protesting a recent decision by the Charlottesville City Council to remove a statue lionizing Confederate General Robert E Lee. On their flyers, the organizers purposely called the location Lee Park even though it had been renamed Emancipation Park. The message was clear: their hero was the defender of slavery, not emancipation.

To be pro-White, you are anti-everything else. It wouldnt be murder to kill them because theyre not even human. (Frohlich, a former White Nationalist)

The hate-group Identity Europa has strict rules about looking and sounding presentable. They are to be well-groomed with clean clothes. They want their men looking manly and their women looking feminine and motherly. They are not to use racial slurs and Nazi rhetoric in public. What is said behind closed doors is quite another matter.

Without hatred of Jews, there would be no movement. (Quote by a White Nationalist)

David Mills explained that the American Alt-Right is just the latest version of an old playbook. The imagery of torches and flags with black eagles on red backgrounds is intentionally reminiscent of the Nazis. Interestingly, participants were discouraged from displaying Hooked Crosses (aka Swastikas) as this symbol might hurt recruitment. While there were some Nazi flags among those who didnt get the memo, most White Supremacists rely on other Nordic Viking symbols such as the Black Sun to get their point across.

Why us? What do they mean when they say that Jews will not replace them?

The terrorists who shot up the Tree of Life Synagogue in Pittsburgh and -closer to home- Chabad of Poway both said that Jews represented the greatest threat to the White Race.

Replacement Theory (frequently espoused by Tucker Carlson) is the idea that demographic shifts, intermarriage and the influx of darker skinned immigrants are threatening to replace the White Race as the dominant force in American society. Jews are the ones pulling those strings because HIAS (Hebrew Immigrant Aid Society), which was originally set up to help Jewish refugees of the pogroms, now helps refugees of all faiths from all over the world.

I asked the panel how to combat the move to normalize propaganda. Dr. Friedberg recommended teaching the camouflage. What do the Nordic symbols really mean? What are their slogans really saying?

I would add that the best way to combat these hate groups is to keep up our good work. The Torah teaches us, Cursed is the one who denies justice to the stranger, the orphaned and the widowed. And all of the people shall respond, Amen. (Deut. 27:19) Therefore, HIAS -and all of us- need to continue welcoming immigrants and befriending those who are different from us. Let us continue to speak up for Freedom and Justice for All. Let us engage in interfaith dialog. We must normalize members of different religions working together and supporting one another when we are attacked.

White Supremacists see themselves as soldiers in a Culture War. Well, if thats what they want, lets give it to them. Let all of the people that they are against- immigrants, ethnic minorities, religious minorities, the disabled and the LGBTQ+- band together. Together we are greater and stronger than they. Let us make it abundantly clear that theirs is the losing side and -like their Civil War- their cause is already lost. And let us say, Amen.

The presentation can be viewed in its entirety by clicking here:https://www.facebook.com/holocaustmuseum

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Eric George Tauber, a former San Diegan now residing in Cincinnati, is a teacher, performer, and a drama critic.He may be contacted via eric.tauber@sdjewishworld.com

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Tracking the Foot Soldiers of White Supremacy - San Diego Jewish World

Eversana ups data and AI power with acquisition of HVH Precision Analytics – Agencies – MM&M – Medical Marketing and Media

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Commercialization giant Eversana has bulked up its data and analytics offering with the acquisition of HVH Precision Analytics from Havas Health & You (HH&Y) and Perspecta. The deal adds a range of data-fueled capabilities, including advanced machine learning and patient identification in rare and misdiagnosed disorders, to Eversanas expanding slate.

The deal comes as somewhat of a surprise, if only because HH&Y leadership had long touted the HVH unit as its secret weapon.

Eversana and HH&Y will, however, continue to work together, with details of what the companies characterized as an exclusive strategic partnership set to be disclosed within the next few weeks.

Were maintaining the relationship with Havas and will expand it, said Brigham Hyde, president, data and analytics at Eversana. He believes, for instance, that the market access/payer and value communications strengths of Eversana Engage pair well with HH&Ys expansive offerings.

Very often were the execution arm of the commercialization process, Hyde explained. A lot of time, the advice and guidance that Havas creates, we end up executing. Having a tighter tie there made a ton of sense. An HH&Y spokesperson did not immediately respond to an emailed request for comment.

The deal came together during the pandemic shutdown, with Eversana one of multiple bidders, Hyde said. After a host of phone calls and Zoom meetings, Hyde and HVH CEO Steve Costalas sorted many of the remaining details at a socially distanced meal in Princeton, NJ. Costalas will remain with the company, though his titleand those of other HVH leadershasnt been finalized. The HVH brand will be formally merged into Eversana before the end of the year.

Given the broad range of activities in which Eversana engages on behalf of its clients everything from running copay programs to servicing specialty pharmacies importing deeper data and analytics expertise is a no-brainer. At the core, what makes those services run well is data and analytics, Hyde said. This is a great building block for what were trying to become, as both a prediction-driven business and a digital business.

HVH Precision Analytics was formally debuted in early 2017 by the predecessor organizations of HH&Y (Havas Health) and Perspecta (Vencore). At the time, then-HVH chief operating officer Jeff Ceitlin noted that the units analytical rigor had been battle-tested, literally, in a different arena. If [Vencore] can use data and analytics to find bad guys in Afghanistan, they can use it to find [undiagnosed] patients, he told MM&M.

In the wake of the acquisition, HVHs 30 or so full-time employees will be integrated into Eversanas data and analytics unit, while its primary Wayne, PA, office will become the 31st outpost in the Eversana global network. The other three locations listed on HVHs website in New York, Boston and Hamilton Township, NJ are Havas network sites that hosted small HVH teams, according to an Eversana spokesperson. Eversana counts more than 2,700 employees around the globe.

Hyde joined Eversana in April. He arrived from Concerto HealthAI, a data and AI startup focused on oncology.

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Eversana ups data and AI power with acquisition of HVH Precision Analytics - Agencies - MM&M - Medical Marketing and Media

AI and Cloud Remove Barriers to Entry for Real-Time Intraday Liquidity – www.waterstechnology.com

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As increasedregulatory reporting obligations add to the pressure financial institutions are under to manage intraday liquidity, centralizing siloed legacy systems into a single automated solution can offer an enterprise-wide, real-time view of liquidity. Richard Morris, product manager, cash and liquidity management at SmartStream, explores how institutions can achieve this, minimizing volatility and performing as efficiently as possible.

Richard Morris, SmartStream

Financial institutions must actively manage their intraday liquidity, but getting to this point continues to be a challenge as banks are required to capture the information they need in real time while meeting increased regulatory reportingobligations.

However, for liquidity risk managers to have a truly relevant enterprise-wide, real-time view of their liquidity, financial institutions will need to consolidate siloed legacy systems into a single automated solution with predictive analytics layered on top.

A report by SmartStream, Intraday Liquidity Management: From a Cost Discussion to a Revenue Opportunity,explores this in detail, as well as how technologies such as cloud, artificial intelligence(AI) and machine learning can help banks achieve higher levels of automation and reduce manualworkload.

Intraday volatility in reporting leads to volatility in decision-making. To manage intraday liquidity successfully in a financial institution, funding, liquidity and risk managers must be able to anticipate the peaks and troughs of the bank balance, and predict the liquidity demands that may occur throughout the day.

Armed with that knowledge, a bank is in control of its own resources rather than responding to settlement demands when they arise. Financial institutions can leverage next-generation technologies such as cloud, AI and machine learning to achieve real-time management of their global intradayliquidity.

The importance of managing the flow of liquidity as well as intraday counterparty exposure cannot be overstated. There is also an element of understanding the drivers of liquidity demand and who within the organisation is driving the demand for intraday liquidity, being able to spot anomalies as they arise and respond to unexpectedevents.

Traditional systems address the operational burden of cash management and consolidating data from internal systems to provide an enterprise-wide view of liquidity demand throughout the day, and of positioning liquidity to meet settlement demands. It is an invaluable task, but it is incredibly data-intensive.

To date, interpreting trends and metrics, and identifying behaviors and anomalies has been hampered by the volume of data being processed and the time it takes to analyze it. Analysis of intraday usage has always been an historical analysis, but technology such as cloud, AI and machine learning can enable banks to take extra value out of the data that results from settlementactivity.

Machine learning allows financial institutions to predict the profiles of their intraday settlement and their peak liquidity demand at any point during the day. Many banks lack this actionable intelligence butusing technology such as machine learning to predict fluctuations in cashflowwill allow financial institutions to manage their flow of liquidity, reducing the liquidity buffer and, in turn, cost.

Predictive analytics can also be used to identify whether the bank or the market as a whole will enter a stressed environment and, therefore, use machine learning to put the organisation in a much better position to respond. These AI and machine learning techniques can also be applied to the regulatory use of data, to help banks derive the maximum benefit from what is beingreported.

The implementation of cloud, on the other hand, enables more institutions to adopt solutions that might otherwise carry a large cost of ownership. Where the largest banks have the resources to develop and operate these advanced solutions, it has always represented a significant investment. The lowering of upfront investment and ongoing costsdriven by the advent of cloud computingwill democratize these solutions and enable much wider uptake across the industry.

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Biggest influencers in AI in Q2 2020: The top companies and individuals to follow – Verdict

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GlobalData research has found the top artificial intelligence (AI) influencers based on their performance and engagement online. Using research from GlobalDatas Influencer platform, Verdict has named ten of the most influential people in artificial intelligence on Twitter during Q2 2020.

Evan Kirstel is a B2B thought leader with extensive experience across enterprises sales, alliances, and business development. He currently serves as chief digital officer and advisor of NYDLA.ORG, a remote, distance/digital learning and collaboration association.

Kirstel is of the opinion that the role of artificial intelligence accelerates the opportunity for increased customer and agent engagement alike. Contact centres are vital for businesses. Overlaying AI, robots and human-guided technology such as gaming is an exciting area.

Twitter followers: 289,645

GlobalData influencer score: 100

Spiros Margaris is a venture capitalist and payment tech consultant. He is also the founder of Margaris Ventures, and serves on the Advisory Board of the wefox Group, a Europe-based insurtech start-up. He is the first international influencer to achieve The Triple Crown ranking.

Margaris has tweeted on varied AI topics such as its assistance in surgical decision- making, the importance of diversity in AI tools, and how companies are spending millions of dollars on the technology.

Twitter followers: 100,490

GlobalData influencer score: 90

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Ronald van Loon is a recognised thought leader in technologies including AI, big data, IoT, machine learning, deep learning, 5G, predictive analytics, cloud, edge and data science. He currently serves as principal analyst and CEO of the Intelligent World, an influencer network that connects experts, businesses, and influencers to new audiences.

Loon is of the opinion that AI has progressed at a furious pace over the past few years, and though it has usurped large chunks of the big data, the technology is nowhere near human intelligence.

Twitter followers: 226,358

GlobalData influencer score: 86

Dr Ganapathi Pulipaka is a chief data scientist and a SAP technical lead at Accenture. With over 20 years of experience in SAP across fields such as project management and technology integration, Ganapathi has worked with various customers on developing AI strategies, neural networks, and other deep learning techniques.

Twitter followers: 92,845

GlobalData influencer score: 82

Kirk Borne is a principal data scientist and advisor at Booz Allen Hamilton, a technology and consulting company in the US. Kirk has been a professor of astrophysics and advisor at the national research labs and government facilities and is known as a top influencer since 2013.

Borne has tweeted on AI topics such as modernising threat detection and analysis with AI tools, and the importance of continued investments in technologies such as AI, cloud, cybersecurity, and others during the global coronavirus pandemic.

Twitter followers: 263,369

GlobalData influencer score: 77

Nigel Willson is a top social media influencer and technologist. He currently serves as the founding partner of awakenAI, a personal advisory company, and is also as the co-founder of We and AI, a non-governmental organisation that focuses on the mission to increase public awareness and understanding of the risks and rewards of AI in the UK.

Ranked as one of the top 20 AI influencers in the world, Nigel is a global speaker, and advisor on artificial intelligence, innovation and technology. He has tweeted on important areas including the ethical risks associated with AI initiatives, the applications of AI in urban management, and more.

Twitter followers: 55,842

GlobalData influencer score: 66

Robert Scoble is a chief strategy officer at Infinite Retina, which helps companies implement spatial computing technologies. A technology strategist and the author of four books on technology, Robert advises companies on areas such as augmented and virtual reality, autonomous vehicles, and associated fields.

Scobles book on how augmented reality and artificial intelligence will change everything delves on discussions and interviews between technologists and business decision makers, and how the technologies will be useful to them.

Twitter followers: 405,477

GlobalData influencer score: 65

Tamara McCleary is the creator of Thulium, a social media analytics and consulting agency. A technology futurist, McCleary is an inspirational keynote speaker, and serves as advisor to leading global tech companies including Amazon, Oracle, Dell, SAP, Cisco, IBM, and Verizon, among others.

According to the influencer, the COVID-19 pandemic has hurried the introduction of artificial intelligence across industries, right from outbreak tracing to contactless customer pay interactions. A change in public sentiment is a possibility, from AI is dangerous to AI is safe.

Twitter followers: 308,431

GlobalData influencer score: 61

Thomas Power is a board member and director of 9Spokes Plc in New Zealand and London based Team Blockchain Ltd. He is also the author of Tokenomics, a book that effectively describes the blockchain shift to cryptocurrencies. He is an author of seven other books and has delivered nearly a thousand speeches across 56 countries.

Twitter followers: 313,005

GlobalData influencer score: 54

Prof Sally Eaves is a global strategy advisor for technologies such as blockchain, AI, and fintech. She specialises in the application and integration of these and other emergent technologies for business and societal benefit. She is also a member of the Forbes Technology Council, and an award winning international keynote speaker, author and influencer.

Eaves is of the opinion that people need to be educated more on AI and blockchain and believes in leveraging AI for societal benefits such as education, healthcare, and more. She also states that automation, AI and communicating over conversational intelligence will be a competitive advantage for businesses during the current health crisis and beyond.

Twitter followers: 107,004

GlobalData influencer score: 53

GlobalData is this websites parent business intelligence company.

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Biggest influencers in AI in Q2 2020: The top companies and individuals to follow - Verdict

How AI Machines Could Save Wall Street Brokers’ Jobs – Entrepreneur

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Morgan Stanleys recentdecision to partner 16,000 financial advisers with algorithms that can identify trades and prod brokers to reach out to clients is evidence of yet another in-road being made by machines into human roles. If brokers embrace this mind-and-machine partnershipthough, the payoff is job security in an industry in which returns are paramount.

The financial services industry is highly Darwinian in nature, with its culture of survival of the best performers. Now, bringing artificial intelligence (AI) into the mix is turning the competition up a notch. The most vulnerable, ironically, could be the high-performing brokers who might be tempted to continue alone without algorithmic assistance. But as weve seen in chess championships likeGarry Kasparov vs. Deep Blue, the supercomputer of its time, or IBMs Watsons victory on Jeopardy!, when human and computer are pitted against each other, the computer wins.

Related: Good, Bad & Ugly! Artificial Intelligence for Humans is All of This & More

As research has shown, however, a human-and-computer collaboration makes an unbeatable combination. Thats whyin business, science or other fields, peoples greatest collaborators are likely to be machines. On Wall Street, if a mediocre broker quickly adopts to using a machine as a partner, he or she will become a formidable performer with increased job security, potentially outperforming the strong broker who refuses to leverage the machine.

Morgan Stanley, one of the worlds biggest brokerages, will roll out its AI pilot to 500 advisers in July. The rest of its brokers will be involved by year-end. The project is being billed as an augmentation of human brokers, not a robo replacement of them.

Automated wealth-management services, known as robo-advisors, are already becoming commonplace among many cost-conscious retail investors, who are gravitating toward computers for inexpensive asset allocation and investment advice. A study in Europe by Fujitsu found that 20 percentof respondents said they would buy banking or insurance services from the likes of Google, Amazonor Facebook. Uber has made a step toward financial services by partnering with GoBank to offer checking accounts and debit cards to drivers.

Related: Why Small Businesses Should Be Paying Attention to Artificial Intelligence

For these digital disruptors, their mastery of machine learning would make it relatively easy for them to enter finance -- arguably far more easily than financial advisers could enter the field of machine learning. This same problem confronted Wall Street in the 1980s when computers first entered the business. At that time, computer scientists grasped the fundamentals of finance with greater ease than finance experts learned the fundamentals of computer programming. By bringing together expertise in each field -- those who know algorithms and those who finance -- Wall Street can offer a high-powered collaboration.

While traditional brokerage services are seen as susceptible to an Uber-like disruption, particularly on the retail end, the high net-worth clientele segment is more likely to be protected -- at least for now due to the importance of relationships.

Yet even here, the mind-and-machine partnership can take the higher end to another level. Algorithms will send brokers multiple-choice recommendations based on market changes or events in a clients life, with the objective of generating more business with customers. But humans are being augmented, not replaced. Bloomberg quoted Jeff McMillan, chief analytics and data officer for Morgan Stanleys wealth-management division, as saying brokers will be needed for the foreseeable future to advise wealthy clients with complicated financial planning needs.

Its analogous to what we see happening in medicine, where AI is being used to enhance physicians clinical knowledge in making diagnoses. One can easily imagine the day when individuals will wear biosensors that produce reams of data that can only be digested by computers to help doctors manage patients health conditions, from diabetes to allergies.

On Wall Street, a machine may excel at making accurate market predictions, but it does so in a black box -- a very dark and unknowable pool for high net worth investors, in particular. These individuals are used to the high-trust relationships such as in private equity, in which there is a premium for explaining how an investment strategy is structured and is expected to perform. Even the most accurate black boxis not likely win the trust of a high-touch client who relies on a human relationship.

Thus, for Wall Streets biggest brokerages such as Morgan Stanley, AI becomes a tool for wealth management. While robo-advisors are embraced by retail investors, high net worth clients who are used to high touch service will still need the human part of the mind-and-machine collaboration. For this clientele, its a matter of trust.

Related: Can Artificial Intelligence Identify Pictures Better than Humans?

But as Morgan Stanley and other Wall Street firms embrace more AI, trust in wealth advisement is likely to become a triangulated relationship. Not only must the two humans -- the client and the adviser -- trust each other, but the two humans (and especially the adviser) must also trust the machine.

For the machine, its about using data and machine learning to make market predictions and identify trade opportunities. For the human, its about relationships and building trust, an area of expertise in which people still have considerable edge over computers.

Brian Uzziis a professor attheKellogg School of Managementat Northwestern University and a globally recognizedscientist and speaker on leadership, social networks and new media. Professor Uzzi was a co-ch...

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Cooperation on Artificial Intelligence will boost security and prosperity on both sides of the Atlantic – NATO HQ

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"There are considerable benefits of setting up a transatlantic digital community cooperating on Artificial Intelligence (AI) and emerging and disruptive technologies, where NATO can play a key role as a facilitator for innovation and exchange", said NATO Deputy Secretary General Mircea Geoan. On Wednesday (28 October 2020) he took part in a high-level virtual discussion on transatlantic cooperation in the era of AI, organised by the Atlantic Council's Future Europe Initiative and GeoTech Center.

Mr. Geoan engaged in this conversation alongside the Chair and Vice Chair of the National Security Commission on Artificial Intelligence (NSCAI), Dr. Eric Schmidt and Secretary Robert O. Work, and the Head of Cabinet of European Commission Executive Vice-President Margrethe Vestager, Ambassador Kim Jrgensen. They discussed what modern technologies mean for European and American defence and security stakeholders, why the United States and the European Union should cooperate on AI, and how best to promote shared values in the field.

"NATO is a natural platform for transatlantic cooperation of AI," the Deputy Secretary General underlined. NATO offers its consultative mechanisms and unique networks for collaboration on defence and security questions. Bringing together Allies and partners, public and private sector, innovators and industry. We have great communities in areas like military capability development, science and technology, standardisation - and of course our Command Structure and military exercises. We also have new cross-cutting policy teams on Innovation Policy, who cover AI, and on Data Policy, he pointed out.

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Cooperation on Artificial Intelligence will boost security and prosperity on both sides of the Atlantic - NATO HQ

How to Reduce Biases in Your Contact Center AI Technology – On the Wire

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How to Reduce Bias: Optimizing AI and Machine Learning For Contact Centers

Bias exists everywhere in our society. And while some biases are largely harmless, like a childs bias towards one food vs the other due to exposure, others are quite destructive. Impacting our society negatively and often resulting in deaths, dispassionate laws, and discrimination. But what happens when the biases that exist in the physical world are hardcoded into the digital? The rise and adoption of artificial intelligence for decision making has already caused alarm in some communities as the impacts of digital-bias play out in front of them every day. In addition, the current events and trends pushing the U.S. and the world towards anti-racism stances and equity regardless of skin color, raises concerns about how societal biases can influence AI, what that means for already marginalized communities, and what companies should be doing to ensure equity in service and offerings to consumers.

Its no news that Artificial Intelligence and Machine Learning are vulnerable to the biases held by the persons that program them1. But, how does bias impact the quality and integrity of the technologies, processes, and more that rely on AI and ML? Covid-19 has hastened the move towards employing these technologies in healthcare, media, and across industries to accommodate for shifts in consumer behavior; new restrictions in the number of personnel allowed in one car, room, or office.

For contact center professionals concerned with ensuring business continuity, improving customer experience, or increasing capacity, the application of AI and ML during these early phases of restructuring due to the pandemic relates to the expansion of capacity, improvement of customer service, and reduced fraud and operational costs. Understanding the consequences of adopting inherently biased AI or ML technologies meant to protect you; the possible impact on your business is necessary as we traverse toward a new normal2 where technology fills the 6ft gap in our society and where fairness and equity will be expected for everyone.

This post discusses bias in artificial intelligence and machine learning reviews the threats to your business this bias causes and presents you with actionable considerations for you to discuss with your team when searching for a contact center anti-fraud or authentication solution.

Bias in artificial intelligence and machine learning can be summarized as the utilization of bad data to teach the machine and thus inform the intelligence. In short, ML bias becomes AI bias through the input and presence of weak data that inform decisions and the encoding of biases based on the thought processes of developers manifesting themselves in algorithmic and societal biases. The inaccuracies caused by these biases can erode trust between the technology and its human users as it is less reliable3. For you, this means less trust, loyalty, and affinity associated with you by consumers.

Includes the aforementioned bad data and is present in many data sets in 1 of 2 ways.

This occurs when the data used to train the algorithm over-represents one population, making it operate better for them at the expense of others4.

For contact centers, a real-world example could be gleaned from AI improperly trained on international calls. For many contact centers, the majority of calls may be domestic- not giving the algorithm enough data relating to international calls may cause bias wherein international calls are flagged for fraud and rerouted to an analyst vs a customer service agent.

Additionally, the machine has to be trained, taught to make a decision. Developers bias algorithms with the ways they interact with them. For example, if we define something as fraud for the machine and teach it that fraud only looks one way with biased inputs, it recognizes fraud committed- as long as it matches the narrow definition it has learned. Combined with selection bias, this results in machines making decisions that are slanted towards one population, while ignoring others3. For a call center professional concerned with fraud mitigation, a real-world form of this bias is an AI systematically ignoring costly fraudster activity and instead focusing on genuine caller behavior and flagging it as suspicious or fraudulent because it doesnt fit the criteria for fraud that the machine has learned.

When choosing a solution for your contact center- you should ask about the diversity and depth of the data being fed to the machine and how it learns over time. Though no solution is infallible, Pindrop works to reduce bias in our AI by making sure that voiceprints are user-specific instead of a generalization based on a large population of persons with similar features, like an accent. Feeding the machine truth gives the machine a more diverse dataset, reducing algorithmic bias.

It is not as quickly defined, tested for, nor resolved4.

This occurs when an algorithm is taught to identify something based on historical data and often stereotypes. An example of this would be an AI determining that someone is not a doctor because they are male. This is due to the historical preponderance of stock imagery featuring male doctors versus those featuring female ones5. The AI is not sexist, the machine has learned over and over that males in lab coats with glasses and badges are doctors; that women can be or should be ignored for this possibility. Pindrop addresses societal bias by developing them using diverse teams. The best applications of AI are those that also include human input. Diversifying human interaction with the machine, the data it is fed, and modeling it is given, strengthens our AI against bias.

Customer Service

Biased solutions could erroneously flag callers as fraudulent. Ruining customer experiences and causing attrition as customers issues take longer to resolve, ultimately costing you monetarily and in brand reputation. An example of this is contact center authentication solutions that use geographic location as a primary indicator of risk. A person merely placing a phone call as they drive could be penalized. Even worse, persons living in risky neighborhoods are at the mercy of their neighbors criminal activity, as biased tech could flag zip codes and unfairly lock out entire populations. Pindrops commitment to reducing bias addresses this impact to customer service using the diverse data sets mentioned above and by applying more complex models for learning. The result is no-one group is more likely than the other to be flagged as fraudulent, suspicious, or otherwise risky. For you, that means less angry callers and false positives overall.

Fraud Costs

As biases can be restrictive for some, locking customers out, other biases coded into your contact center antifraud or authentication solution can allow more fraud through as it makes certain assumptions. For example, for years6 data has pointed towards iPhone users being more affluent than Android users. For contact center professionals, should your solution make assumptions that wealthier consumers are more trustworthy than working-class persons, it may lower the score of fraudsters on iPhone, possibly allowing the perpetrators into accounts and systems while over penalizing Android users. Though Pindrop is not immune to bias no solution is we can greatly reduce the AI biases that can increase fraud costs unintentionally, through our approach to developing AI.

Contact Center Operations

Lastly, a biased solution could cost you in productivity and operational costs. The two examples above can quickly impact your productivity, costing you more per call. AI biases could cause you to implement step-up authentication for genuine callers and flag accounts exhibiting normal behavior as suspicious because of an encoded logarithmic or societal bias.

Solutions like Pindrops single platform solutions for contact center security help improve customer experience, reduce fraud costs, and optimize contact center operations by developing proprietary AI that learns from diverse and purely fact-based inputeliminating bias in the AI.

Bias enters AI and ML via corrupt data practices but also from the way the solutions are built5. But there are ways to address the builders biases and shield the solution from the input of bad data. In this section, there are 3 core principles to remember when searching for a solution employing AI or machine learning.

Now that you understand how a biased AI can impact your business, you should consider 3 core principles when searching for a solution to serve your contact center. Your ideal solution should:

Have diverse, varied, and fact-based inputs

Diverse, varied, and fact-based inputs address selection bias and ensure that all populations are sampled and therefore considered in calculations that become decisions. For example,

Understand Garbage In, Garbage Out

Question your solutions data inputs. Utilizing outdated concepts, naming conventions, and more influences your machine to make decisions that are prejudiced against specific population segments. Understanding the data inputs and freshness of the data ingested by your solution helps fight against latent bias in AI. For example, earlier in this post we discussed latent bias. This kind of bias is based on societal norms or rather accepted societal behaviors at the time. With that in mind, think of an engine deciding college admissions, based on the admissions of the past 60 years. Its 2020 in 1960 many public and private schools where still racially segregated. In the event that this data is fed to the engine, it will most certainly weigh an applicants race negatively.

Everyone Has Biases

The goal should be neutrality, and diverse views bring us closer to an optimal state of development. By combining varied voices, thought processes, and capabilities from diverse groups of developers, an AI could be created with such diverse and varied inputs, that it learns to operate outside of the conflicting biases of its makers. For example, above, we explained how societal influences even those no longer widely accepted could impact AIs decisions. Should the AI ingest historic information polluted with outdated thought processes, naming conventions, and other latent biases but is also fed fresh, diverse data by diverse humans, it will gain via feedback from the humans, deep learnings to help it make more nuanced, accurate, and less biased decisions.

When considering an AI-powered solution for the protection of your contact center and customers, understanding bias in AI and ML, how it impacts your business, and what you can do about it ultimately saves you time, reduce costs, and hardens your contact center to attack.

Pindrops single-platform solutions for the contact center can help you address challenges in fraud mitigation and identity verification. These solutions are fed fact-based inputs, follow proprietary data collection and analysis processes, and are built by diverse and capable teams to help eliminate bias from our software. Contact us today to see it in action, or learn more from our resource pages.

IEEE, Spectrum. Full Page Reload. IEEE Spectrum: Technology, Engineering, and Science News, 2019, spectrum.ieee.org/tech-talk/tech-history/dawn-of-electronics/untold-history-of-ai-the-birth-of-machine-bias.

Radfar, Cyrus. Bias in AI: A Problem Recognized but Still Unresolved. TechCrunch, TechCrunch, 25 July 2019, techcrunch.com/2019/07/25/bias-in-ai-a-problem-recognized-but-still-unresolved/.

Howard, Ayanna, and Jason Borenstein. AI, Robots, and Ethics in the Age of COVID-19: Ayanna Howard and Jason Borenstein. MIT Sloan Management Review, 12 May 2020, sloanreview.mit.edu/article/ai-robots-and-ethics-in-the-age-of-covid-19/.

Gershgorn, Dave. Google Explains How Artificial Intelligence Becomes Biased against Women and Minorities. Quartz, Quartz, 28 Aug. 2017, qz.com/1064035/google-goog-explains-how-artificial-intelligence-becomes-biased-against-women-and-minorities/.

Hao, Karen. This Is How AI Bias Really Happens-and Why Its so Hard to Fix. MIT Technology Review, MIT Technology Review, 2 Apr. 2020, http://www.technologyreview.com/2019/02/04/137602/this-is-how-ai-bias-really-happensand-why-its-so-hard-to-fix/.

Yahoo Finance. These Maps Show That Android Is For Poor People. Yahoo! Finance, Yahoo!, 4 Apr. 2014, finance.yahoo.com/news/maps-show-android-poor-people-000200949.html.

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How to Reduce Biases in Your Contact Center AI Technology - On the Wire

Google and ZebiAI launch Chemome Initiative to identify chemical probes with AI models – VentureBeat

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In a study published this week in the Journal of Medicinal Chemistry, researchers at Google, in collaboration with X-Chem Pharmaceuticals, demonstrated an AI approach for identifying biologically active molecules using a combination of physical and virtual screening processes. It led to the creation of the Chemome Initiative, which launches today a collaboration between Googles Accelerated Science team and startup ZebiAI that aims to enable the discovery of many more small molecule chemical probes for biological research.

As part of the Chemome Initiative, Google says that ZebiAI will work with researchers to identify proteins of interest and source screening data the Accelerated Science team will use to train AI models. These models will make predictions on commercially available libraries of small molecules chemical probes that arent useful as drugs, but that selectively inhibit or promote the function of specific proteins that will be provided to researchers for activity testing to advance some programs through discovery.

Making sense of the biological networks that support life and produce disease is a complex task. One approach is using small molecules; in a biological system (e.g., cancer cells growing in a dish), they can be added at a specific time to observe how the system responds when a protein has increased or decreased activity.

Despite how useful chemical probes are for this kind of biomedical research, only 4% of human proteins have a known chemical probe available. In an effort to isolate new ones, Google and X-Chem Pharmaceuticals turned to the field of AI and machine learning.

As the coauthors of the study explain, chemical probes are identified by scanning the space of small molecules in a target protein to distinguish hit molecules that can be further tested. The physical part of the process uses DNA-encoded small molecule libraries (DELs) that contain many distinct small molecules in one pool, each of which is attached to a fragment of DNA serving as a barcode for that molecule. One generates many chemical fragments along with a common chemical handle. The results are pooled and split into separate reactions, where a set of distinct fragments with another chemical handle are added.

The chemical fragments from the two steps react and fuse together at the common chemical handles, and theyre connected to build one continuous barcode for each molecule. Once a library has been generated, it can be used to find the small molecules that bind to the protein of interest by mixing the DEL with the protein and washing away the small molecules that dont attach. Sequencing the remaining DNA barcodes produces millions of individual reads of DNA fragments that can then be processed to estimate which of the billions of molecules in the original DEL interact with the protein.

Above: The fraction of molecules from those tested showing various levels of activity, comparing predictions from the classifier and random forests on three protein targets.

Image Credit: Google

To predict whether an arbitrarily chosen small molecule will bind to a target protein, the researchers built a machine learning model specifically a graph convolutional neural network, a type of model designed for graph-like inputs like small molecules. The physical screening with the DEL provides positive and negative examples for a classifier, such that the small molecules remaining at the end of the screening process are positive examples and everything else is negative examples.

The team physically screened three diverse proteins using DEL libraries: sEH(a hydrolase),ER(a nuclear receptor), andc-KIT (a kinase). Using the DEL-trained models, they then virtually screened large make-on-demand libraries from drug discovery platform Mculeand an internal molecule library atX-Chem to identify a set of molecules predicted to show affinity with each protein target. Lastly, they compared the results of their classifier to a random forest model, a common method for virtual screening that uses standard chemical fingerprints. They report that the classifier significantly outperformed the RF model in discovering potent candidates.

The team tested almost 2,000 molecules across the three targets, which it claims is the largest published prospective study of virtual screening to date.

Were excited to be a part of the Chemome Initiative enabled by the effective ML techniques described here and look forward to its discovery of many new chemical probes. We expect the Chemome will spur significant new biological discoveries and ultimately accelerate new therapeutic discovery for the world, Google wrote in a blog post. While more validation must be done to make the hit molecules useful as chemical probes, especially for specifically targeting the protein of interest and the ability to function correctly in common assays, having potent hits is a big step forward in the process.

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Google and ZebiAI launch Chemome Initiative to identify chemical probes with AI models - VentureBeat

WIMI Holographic Academy Invest More in AI Technology Research, Holographic Technology Achieves Breakthrough in Mobile Interaction – GlobeNewswire

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HONG KONG, May 28, 2021 (GLOBE NEWSWIRE) -- MobiusTrend, the fintech market research organization, recently released a research report "WIMI Holographic Academy Invest More in AI Technology Research, Holographic Technology Achieves Breakthrough in Mobile Interaction". With the continuous development of holographic technology, its application range is getting wider and wider. At the same time, in order to bring the audience a more extreme sense of experience and dig deeper into holographic R&D resources, outstanding scholars at home and abroad have successively invested in various special research and explored cutting-edge technologies.

According to a new study by the Holographic Research Group of Brigham Young University, they have found a way to create a lightsaber. Namely, Yoda is green, Darth Vader is red, which naturally produces a luminous beam. This discovery overcomes a long-standing challenge in this field and brings a new concept of interaction to holographic technology.

We should understand a concept firstly, that is, what is the concept of interaction? It is generally believed that interaction takes people as the main body, and people exchange information with other things, and produce interaction and influence. The two will produce a process of information exchange, which may be unilateral or bilateral. Objectively speaking, interaction contains multi-level and multi-dimensional attributes. With the continuous innovation of information technology, computer technology, virtual technology, and imaging technology, the concept of interaction is also changing subtly, and the continuous update of the concept of interaction will expand people's thinking and promote the diversification of interaction methods.

An interview with one of the researchers, Professor of Electrical Engineering of BYU, Dan Smalley, said: "What they see in the scenes they create is real; there is no computer-generated." It is not like movies, either lightsabers or photon torpedoes never really exist in physical space. They are real and can even make simple animations in thin air. The development paves the way for immersive experiences, where people can interact with holographic-like virtual objects that coexist in their direct space. To prove this principle, the team also created virtual stick figures who can walk in the air.

It can be said that the emergence of brand-new interactive concepts has changed people's stereotypes to a certain extent and brought new enlightenment. Its innovation is a key factor for the development of the holographic industry, especially its use in holographic imaging technology. Through the holographic image, the audience can enter a brand-new situation. In addition to watching, the audience can also feel the situation and get a new experience. This "spatial reconstruction" model allows the interactive subject to directly occupy the active position in the context. Holographic images have made human-computer interaction more thorough, enhanced the communication between the product and the audience, allowed the audience to have a deeper understanding of the product, and established the behavioral relationship between the product and the person. At the same time, with the help of holographic images, designers can express the design concepts and thoughts contained in the product to the audience, so that the audience can resonate in thought.

The characteristics of the new interactive concept under the holographic imaging technology are presented as follows. (1) Diversity. In the process of human perception of the surrounding environment, vision and hearing have a complementary effect on each other. Holographic imaging technology fully integrates voice and vision. On the basis of voice interaction, the interaction breaks the shackles of 2D and transforms into a three-dimensional interaction. Even some special interactive media can provide the audience with the sense of smell, touch, and taste based on the sense of sight and hearing. The diversified experience makes the interaction efficiency to a higher level. (2) Visualization. The virtual environment brings hearing and visual feelings to people. However, due to the lack of tactile feel it still has a certain gap with the real feelings. This is also one of the limitations of virtualized interaction. The holographic image is associated with force feedback. When the user touches the image, a special force feedback device will feed back information to the user, allowing the user to get a more intuitive experience. (3) A large amount of information. Compared with traditional media, holographic images carry a greater amount of information. The digital image is refined by computing software, and multiple holographic images can be superimposed to form a digital virtual space, which carries a lot of information. It is also based on this large-capacity information that brings a fuller interactive experience to the audience.

In order to promote in-depth cooperation with academia, explore holographic cutting-edge technologies with scholars at home and abroad, promote the implementation of the industry, and open up research results, this time, the WIMI Holographic Academy of Sciences also continues to research on the AI cutting-edge technology and establish strategic partnerships with scholars from research institutions. WIMI aims to explore disruptive emerging technologies together with them to accelerate the application and promotion of research results. In 2020, relying on the research teams in Shenzhen and Beijing, the WIMI Holographic Academy of Sciences has opened four research themes of holographic computing science, holographic communication science, micro-integration science, and holographic cloud science. Relying on the team strength of the WIMI Holographic Academy of Sciences, it is actively promoting the research and development of holographic products. WIMI is looking forward to exploring the unknown AI cutting-edge technology with outstanding scholars from universities or scientific research institutions at home and abroad, and to creating a sustainable and win-win AI industry-university cooperation research ecosystem. The fineness of image information obtained by WIMI holographic computer vision AI synthesis is about 10 times higher than the industry level, and the processing capability of computer holographic vision AI synthesis is about 80% better than the industry average.

At present, artificial intelligence technology is widely used in various Internet applications, enterprise-level applications, and emerging intelligent hardware scenarios. Namely, AI has penetrated all walks of life. From 2020, the scale of China's core artificial intelligence industry will be close to 65 billion yuan, involving many fields such as security, finance, medical care, and education. Facing different application requirements, artificial intelligence technology has spawned a variety of different machine learning algorithms, such as deep learning, active learning, and reinforcement learning, aiming to bring more extreme experience and greater capacity.

WIMI emphasizes both research and application development, and its basic research focuses on machine learning, computer vision, and other directions. Also, it has published many research papers, and its technology applications focus on social, gaming, education, medical AI, and other fields. In terms of cloud computing, artificial intelligence, the Internet of Things, and other frontier technology fields, WIMI Hologram Cloud also relies on global and Chinese technology and business networks, and it has successively invested in companies in related fields, attracting many innovative companies, partners, and innovative talents. In the future, it is believed that WIMI will play a more important role in the application space and bring humans a better AI interactive experience.

About MobiusTrend

MobiusTrend Group is a leading market research organization in Hong Kong. They have built one of the premier proprietary research platforms on the financial market, emphasizing on emerging growth companies and paradigm-shifting businesses. MobiusTrend team is professional in market research reports, industry insights, and financing trends analysis. For more information, please visit http://www.mobiustrend.com/

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WIMI Holographic Academy Invest More in AI Technology Research, Holographic Technology Achieves Breakthrough in Mobile Interaction - GlobeNewswire

14 ways AI will impact the education sector – VentureBeat

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There have been a lot of digital next big things in education over the years everything from the Apple IIe to online learning. The latest is artificial intelligence education tech (AI Ed), and only time will tell what impact it ultimately has. But for something as important as education, now is the time to start talking about the benefits and challenges created by the AI-powered personalized learning systems that are making their way into classrooms.

Entefy covered this topic in previous articles: Old school no more: AI disrupts the classroom, which focused on teachers; and Artificial intelligence may transform education, but are parents ready?, which focused on parents.

The clear near-term opportunity for AI Ed is to support teachers by taking over time-consuming, lower-value tasks, like grading and record keeping. But there are already sophisticated AI teaching systems under development, systems that raise long-term questions about what place AI should have in schools.

Here are 14 unprecedented benefits and challenges that could arise:

AI has the potential to change the quality, delivery, and nature of education. It also promises to change forever the role of parents, students, teachers, and educational organizations.

Additional article contributors: Mehdi Ghafourifar and Brian Walker.

Alston Ghafourifar is the CEO and Co-Founder ofEntefy, an AI-communication technology company, which makes the first universal communicator.

The article originally appeared atEntefy.

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HarperCollins Brings AI To Book Recommendations – Forbes

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Forbes
HarperCollins Brings AI To Book Recommendations
Forbes
Publishers have always emphasized the power of word-of-mouth marketing when it comes to selling books. Booksellers are expected to hand-sell titles to bookstore patrons for this reason, and the shelves are often peppered with "employee recommendation" ...

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HarperCollins Brings AI To Book Recommendations - Forbes

Deepfakes and the New AI-Generated Fake Media Creation-Detection Arms Race – Scientific American

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Falsified videos created by AIin particular, by deep neural networks (DNNs)are a recent twist to the disconcerting problem of online disinformation. Although fabrication and manipulation of digital images and videos are not new, the rapid development of AI technology in recent years has made the process to create convincing fake videos much easier and faster. AI generated fake videos first caught the public's attention in late 2017, when a Reddit account with the name Deepfakes posted pornographic videos generated with a DNN-based face-swapping algorithm. Subsequently, the term deepfake has been used more broadly to refer to all types of AI-generated impersonating videos.

While there are interesting and creative applications of deepfakes, they are also likely to be weaponized. We were among the early responders to this phenomenon, and developed the first deepfake detection method based on the lack of realistic eye-blinking in the early generations of deepfake videos in early 2018. Subsequently, there is a surge of interest in developing deepfake detection methods.

DETECTION CHALLENGE

A climax of these efforts is this years Deepfake Detection Challenge. Overall, the winning solutions are a tour de force of advanced DNNs (an average precision of 82.56 percent by the top performer). These provide us effective tools to expose deepfakes that are automated and mass-produced by AI algorithms. However, we need to be cautious in reading these results. Although the organizers have made their best effort to simulate situations where deepfake videos are deployed in real life, there is still a significant discrepancy between the performance on the evaluation data set and a more real data set; when tested on unseen videos, the top performers accuracy reduced to 65.18 percent.

In addition, all solutions are based on clever designs of DNNs and data augmentations, but provide little insight beyond the black boxtype classification algorithms. Furthermore, these detection results do not reflect the actual detection performance of the algorithm on a single deepfake video, especially ones that have been manually processed and perfected after being generated from the AI algorithms. Such crafted deepfake videos are more likely to cause real damage, and careful manual post processing can reduce or remove artifacts that the detection algorithms are predicated on.

DEEPFAKES AND ELECTIONS

The technology of making deepfakes is at the disposal of ordinary users; there are quite a few software tools freely available on GitHub, including FakeApp, DFaker, faceswap-GAN, faceswap and DeepFaceLabso its not hard to imagine the technology could be used in political campaigns and other significant social events. However, whether we are going to see any form of deepfake videos in the upcoming elections will be largely determined by non-technical considerations. One important factor is cost. Creating deepfakes, albeit much easier than ever before, still requires time, resources and skill.

Compared to other, cheaper approaches to disinformation (e.g., repurposing an existing image or video to a different context), deepfakes are still an expensive and inefficient technology. Another factor is that deepfake videos can usually be easily exposed by cross-source fact-checking, and are thus unable to create long-lasting effects. Nevertheless, we should still be on alert for crafted deepfake videos used in an extensive disinformation campaign, or deployed at a particular time (e.g., within a few hours of voting) to cause short-term chaos and confusions.

FUTURE DETECTION

The competition between the making and detection of deepfakes will not end in the foreseeable future. We will see deepfakes that are easier to make, more realistic and harder to distinguish. The current bottleneck on the lack of details in the synthesis will be overcome by combining with the GAN models. The training and generating time will be reduced with advances in hardware and in lighter-weight neural network structures. In the past few months we are seeing new algorithms that are able to deliver a much higher level of realism or run in near real time. The latest form of deepfake videos will go beyond simple face swapping, to whole-head synthesis (head puppetry), joint audiovisual synthesis (talking heads) and even whole-body synthesis.

Furthermore, the original deepfakes are only meant to fool human eyes, but recently there are measures to make them also indistinguishable to detection algorithms as well. These measures, known as counter-forensics, take advantage of the fragility of deep neural networks by adding targeted invisible noise to the generated deepfake video to mislead the neural networkbased detector.

To curb the threat posed by increasingly sophisticated deepfakes, detection technology will also need to keep up the pace. As we try to improve the overall detection performance, emphasis should also be put on increasing the robustness of the detection methods to video compression, social media laundering and other common post-processing operations, as well as intentional counter-forensics operations. On the other hand, given the propagation speed and reach of online media, even the most effective detection method will largely operate in a postmortem fashion, applicable only after deepfake videos emerge.

Therefore, we will also see developments of more proactive approaches to protect individuals from becoming the victims of such attacks. This can be achieved by poisoning the would-be training data to sabotage the training process of deepfake synthesis models. Technologies that authenticate original videos using invisible digital watermarking or control capture will also see active development to complement detection and protection methods.

Needless to say, deepfakes are not only a technical problem, and as the Pandoras box has been opened, they are not going to disappear in the foreseeable future. But with technical improvements in our ability to detect them, and the increased public awareness of the problem, we can learn to co-exist with them and to limit their negative impacts in the future.

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MJ or LeBron Who’s the G.O.A.T.? Machine Learning and AI Might Give Us an Answer – Built In Chicago

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Our country is deeply divided into two camps.

From coast to coast, people are eager to know the answer to one simple question: Who will come out on top Michael Jordan or LeBron James?

It might seem like a moot point. NBA legend Michael Jordan is now well into retirement while LeBron James is still able to continue building his case with the Los Angeles Lakers. Thanks to the laws of time and space, theres no way to accurately compare their talent in a conclusive way.

Or is there?

AutoStats, a product of Stats Perform, is using artificial intelligence and computer vision to unlock secrets of seasons past and predict seasons future.

The goal of AutoStats is to collect tracking data from every sports video that has ever existed which essentially enables us to travel back in time and compare players and eras in a way that we havent been able to do previously, said Patrick Lucey, chief scientist at Stats Perform. Using this technology, we can start to make the impossible possible.

The implications of these statistics are a real game-changer in the sports world, the effects of which can be seen in betting, team drafting and recruitment, professional commentary, fantasy football and how well your opinions on all-star players hold up.

Sujoy Ganguly, Ph.D.

Director of Computer Vision

I am the director of computer vision, which means I teach computers to watch sports. Specifically, we extract the positions of the players, their limbs and actions directly from the broadcast video you get in your home.

Patrick Lucey, Ph.D.

Chief Scientist

Im the chief scientist, and my role is to set the AI strategy to maximize the value of our deep treasure troves of sports data using AI technology.

Patrick Lucey: AI not only emulates what a human can do, but surpasses what even the best human expert can do. The reason why artificial intelligence has reached this superhuman capability is that it has utilized an enormous amount of data. The more data you have, the better your AI technology will be simple as that.

When it comes to the sheer volume of sports data, no other company has the amount that we have. We cover any sport you can think of, and we capture it at a depth that no other company does.

Sujoy Ganguly: The goal of our team is to create the most in-depth data at the broadest breadth. We do this by extracting player tracking, pose and event data everywhere there is broadcast video. To accomplish this, we have three streams:one that focuses on model development, the second that focuses on the deployment of these models to the cloud, and a third that focuses on implementation at the edge for in-venue deployment.

How does Stats Perform get its data?

Stats Perform collects data through raw video. Its collected via the companys in-venue hardware or snapped up from broadcasts.

Lucey: Well, its like teaching a child how to read. First, they have to learn the alphabet and words before being able to understand a sentence, then onto a paragraph only then they can understand the whole story. Once they have read a lot of books and seen similar stories in the past, then they can actually start to predict how the story will unfold.

Its similar for sport, where we first have to create a sports-specific alphabet and words from which to form sentences that represent gameplay that a computer can understand. Instead of using characters and textual words, we use spatial data and event sequences. From this sports-specific language we have built, we can then get the computer to learn similar gameplay from the data we have, which enables us to predict plays and player motion. The main reason why I believe AI has so much hype around it is that it is the ultimate decision analysis tool every decision and action can be objectively analyzed.

Ganguly: Teaching a machine to interpret sports is a complex and evolving problem. At a high level, we start with a clearly defined question. For example, what is the likelihood that a team will win a game, and how does this depend on the players on that team? Then we ask what information we have: We have results of thousands of games and data about the players who played in those games. From there, we can start the process of conducting experiments and converging to a high-performing model. Generally, this process requires an open and honest conversation about the results of each test and what we have learned.

Ganguly: Many of the challenges we face with machine learning are the same as in other industries, like how we collect and maintain data sets or how we manage training and deployment workloads. However, most companies that work on prediction are doing so on strictly temporal data. In contrast, we have spatial and temporal information. Unlike the autonomous vehicle companies that also deal with spatial-temporal data, we dont control all of the sources of video. This presents unique challenges in data collection but also allows us to use predictive models that allow for noise and are therefore robust.

Different kinds of data

Temporal data is data relating to time and spatial data refers to space. As Ganguly alluded to, combining the two is necessary in the tech behind self-driving cars. This data helps determine whats another moving object, like another car, and whats stationary, say, a tree. For Stats Perform, they data scientists are looking less at a deer in the road, and more how a player moves on the field, and at what speed. The result is the ability to pinpoint the specific motions of a player depending on the context of the game and play, and to anticipate how theyd react in a similar situation.

Lucey: The example I like to talk about is our work in soccer. Soccer is a hard sport to analyze because it is low-scoring, continuous and strategic. As such, the current statistics used, such as possession percentage, number of passes and completion rate, number of corners and tackles, do not correlate with goals scored and who won the match. Our AI-based metrics expected goals, quality of passes and playing styles correlate much higher with goals compared to standard statistics. These AI-metrics simply measure performance better. Using these AI tools, we were able to show how, against incredible odds, underdog Leicester City won the 2015-16 English Premier League title.

Ganguly: There are two significant ways that AI is and will continue to revolutionize sports. Firstly, AI is creating more complex and granular data at an unprecedented scale. For example, with our AutoSTATS technology, we can capture the motions of players in college basketball, where this data was never before available. The other way AI is revolutionizing sport is by allowing people to draw insights from our increasingly in-depth data. Using player tracking data, we can predict the motion of players. This allows us to see how a player will behave on their team after a trade, thereby allowing for better player recruitment.

Isolating a teams formation

Tools like Stats Performsunsupervised clustering method can quickly find a teams formation right down to the frame. When humans attempt to do this, their results fall just a few yards short.

Lucey: Even though we have the most sports data on the planet, to tell the best stories and provide the best analysis and products for our customers, we need even more granular data. Thats why I am so excited about our AutoStats work.

AI has so much hype around it is because it is the ultimate decision analysis tool every decision and action can be objectively analyzed. AI can not only capture data using computer vision and other sensors that couldnt be captured before, but it can help us transform that data into a form that can be used to make decisions. Given how popular sports are around the world and the importance they have on other sectors, theres potential for other industries to directly use the data and technology that we have generated to make future decisions.

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MJ or LeBron Who's the G.O.A.T.? Machine Learning and AI Might Give Us an Answer - Built In Chicago

Tesla AI Day Starts Today. Here’s What to Watch. – Barron’s

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Former defense secretary Donald Rumsfeld said there are known knownsthings people knowknown unknownsthings people know they dont knowand unknown unknownsthings people dont realize they dont know. That pretty much sums up autonomous driving technology these days.

It isnt clear how long it will take the auto industry to deliver truly self-driving cars. Thursday evening, however, investors will get an education about whats state of the art when Tesla (ticker: TSLA) hosts its artificial intelligence day.

The event will likely be livestreamed on the companys website beginning around 8 p.m. Eastern Standard Time. The companys YouTube channel will likely be one place to watch the event. Other websites will carry the broadcast as well. The company didnt respond to a request for comment about the agenda for the event, but has said it will be available to watch.

Much of what will get talked about wont be a surprise, even if investors dont understand it all. Those are known unknowns.

Tesla should update investors about its driver assistance feature dubbed full self driving. Whats more, the company will describe the benefit of vertical integration. Tesla makes the hardwareits own computers with its own microchipsand its software. Tesla might even give a more definitive timeline for when Level 4 autonomous vehicles will be ready.

Roth Capital analyst Craig Irwin doesnt believe Level 4 technology is on the horizon though. He tells Barrons the computing power and camera resolution just isnt there yet. Tesla will work hard to suggest tech leadership in AI for automotive, says Irwin. Reality will probably be much less exciting than their claims.

Irwin rates Tesla shares Hold. His price target is just $150 a share.

The car industry essentially defines five levels of autonomous driving. Level 1 is nothing more than cruise control. Level 2 systems are available on cars today and combine features such as adaptive cruise and lane-keeping assistance, enabling the car to do a lot on its own. Drivers, however, still need to pay attention 100% of the time with Level 2 systems.

Level 3 systems would allow drivers to stop paying attention part of the time. Level 4 would let them stop paying attention most of the time. And Level 5 means the car does everything always. Level 5 autonomy isnt an easy endeavor, says Global X analyst Pedro Palandrani. There are so many unique cases for technology to tackle, like in bad weather or dirt roads. But level 4 is enough to change the world. he added. He is more optimistic than Irwin about the timing for Level 4 systems and hopes Tesla provides more timing detail at its event.

Beyond a technology run down and level 4 timing, the company might have some surprises up its sleeve for investors. Palandrani has two ideas.

For starters, Tesla might indicate its willing to sell its hardware and software to other car companies. That would give Tesla other unexpected, sources of income. Tesla already offers its full self driving as a monthly subscription to owners of its cars. Thats new for the car industry and opens up a source of recurring revenue for anyone with the requisite technology. Selling hardware and software to other car companies, however, would be new, and surprising, for investors.

Tesla might also talk about its advancements in robotics. CEO Elon Musk has talked often in the past about the difficulty of making the machine that makes the machine. Some of Teslas AI efforts might also be targeted at building, and not just driving, vehicles. Were just making a crazy amount of machinery internally, said Musk on the companys second-quarter conference call. This is.not well understood.

Those are two items that can surprise. Whether they, or other tidbits, will move the stock is something else entirely.

Tesla stock dropped about 7% over Monday and Tuesday partly because NHTSA disclosed it was looking into accidents involving Teslas driver assistance features. Tesla will surely stress the safety benefits of driver assistance features on Thursday, whether it can shake off that bit of bad news though is harder to tell.

Thursday becomes a much more important event in light of this weeks [NHTSA] probe, says Wedbush analyst Dan Ives. This week has been another tough week for Tesla [stock] and the Street needs some good news heading into this AI event.

Ives rates Tesla shares Buy and has a $1,000 price target for the stock. Teslas autonomous driving leadership is part of his bullish take on shares.

If history is any guide investors should expect volatility. Tesla stock dropped 10% the day following its battery technology event in September 2020. It took shares about seven trading days to recover, and Tesla stock gained about 86% from the battery event to year-end.

Tesla stock is down about 6% year to date, trailing behind the 18% and 15% comparable, respective gains of the S&P 500 and Dow Jones Industrial Average. Tesla stock hasnt moved much, in absolute terms, since March. Shares were in the high $600s back then. They closed down 3% at $665.71 on Tuesday, but are up 1.3% at $674.19 in premarket trading Wednesday.

Write to allen.root@dowjones.com

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Tesla AI Day Starts Today. Here's What to Watch. - Barron's

AI Technology Can Enhance Human-Centered Work Instead Of Threaten It – Forbes

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AI company Samasource is advocating a human-in-the-loop, model that requires human involvement ... [+] with its advanced technology.

Whenever new technologies change the way we work, some worry that their jobs are in jeopardy. And sometimes, new technologies do make certain jobs obsolete. Artificial intelligence is an emerging force in the business world that has the potential to either replace humans in certain industries or empower humans with better tools, depending on how the technology is utilized. And in the high-unemployment COVID era when the terms outsourcing and AI stoke fears for workforce stability and opportunity, there needs to be a more human-centered approach to workforce training and development.

Samasource, a training data and validation company based in San Francisco, believes AI can enhance how we work and is advocating for human-in-the-loop, a work model that requires human involvement even with advanced technology. It's really this combination of human and artificial intelligence, or human-in-the-loop and machine learning, that will allow us to bring best-in-class technology to solve the world's most pressing challenges, says Heather Gadonniex, the VP of Marketing & Strategic Partnerships at Samasource.

I spoke with Gadonniexas part of my research on purpose-driven businessand to learn about how Samasource is using its advanced technology to enhance human-centered work and provide job opportunities to marginalized communities. Samasource is a Certified B Corporation, a company that has met certain social and environmental standards as verified by the nonprofit B Lab.

Christopher Marquis: Some people worry that artificial intelligence will ultimately replace humans in the workforce. How is Samasource ensuring that AI is used to enhance human-centered work and not fully replace it?

Heather Gadonniex, VP of Marketing & Strategic Partnerships at Samasource.

Heather Gadonniex: Our philosophy is to use artificial intelligence to power and empower the human workforce. We firmly believe in up-skilling. We firmly believe in cross-skilling. And we firmly believe that artificial intelligence, or machine learning, is not necessarily going to negate the need for human involvement but will simply remove more mundane tasks from day-to-day workloads so that humans can focus on tasks that require higher cognition and focus on higher value areas of work.

It's really this combination of human and artificial intelligence, or human-in-the-loop and machine learning, that will allow us to bring best-in-class technology to solve the world's most pressing challenges. And in my opinion, we have enough challenges that need to be solved that we shouldn't shy away from using the power of technology to do that.

We're really embracing, advocating for, and being a voice in the market for this combination of machine intelligence and human intelligence, and at the same time ensuring that there is up-skilling and that there is cross-skilling. Because without that, you don't really have the ability to create environments or workplaces where people are learning the new skills they need to thrive in the next digital economy, or in today's digital economy even. That's really how we perceive this conflict between human and machine, if you will less of a conflict and more of a collaboration.

Marquis: Can you share examples of up-skilling? What does that look like in practice?

Gadonniex: We have a very robust education program internally, called SamaU. So we use a combination of technology platforms plus face-to-face training, and we provide basic digital skills to get people familiarized with working in the digital economy. Because the majority of the workforce that we employ have never had a formal job before they are working in areas that are typically not exposed to the digital economy. For most of them, this is their first full time job that pays living wages. And that, in and of itself, has the power to transform economies, not just lives but full economies.

So, we provide our workers with basic digital skills, and then from there we actually provide ongoing training around topics that focus on machine learning, general artificial intelligence, and soft skills as well, like: How do you manage your finances? How do you become a better boss? How do you work in a professional environment? Many of them have never had the opportunity to learn how to actually manage a paycheck. Oftentimes, they've never even had a steady paycheck. So that soft skill training is equally important to the digital up-skilling and the technology skill training.

We also just completed a randomized control trial with MIT to validate the efficacy of this model. People who received training and employment at Samasource reported 10% lower unemployment rates and wages that are, on average, more than 25% higher than our control group. Our up-skilling programs, our full-time employment programs, and paying living wages had a particularly significant effect on women who received earnings 30% higher than the control group. If you look at economic development as a whole, that is so powerful.

Marquis: How has your business adapted during COVID? And do you have any recommendations for other businesses looking to adapt to these challenges?

Gadonniex: We launched multiple initiatives through 2020 to ensure our employees were able to safely maintain their jobs and continued to deliver the secure, high quality training data that we're known for in the midst of this pandemic. Business continuity was extremely high on the priority list of our customers, especially during the start of COVID. And I think that that makes total sense given the situation.

To ensure continuity, we create a program called Samahome, a partnership between Samasource and local hotels in Kenya and Uganda. We enabled our employees to work in safe environments during the height of the pandemic in these live-work arrangements.

Our team members could opt in to live and work at Samahome. Before they entered the Samahome, everyone was checked to make sure they were healthy. We conducted ongoing health checks, practiced social distancing, and ensured that there were sanitization measures in place.

We recently launched our work-from-home initiative, which actually provides our employees with the necessary resources to effectively work from home. We also have a few teams that are starting to work from our secured delivery centers again, and we're continuing to transition back for certain teams while maintaining social distancing protocols and health checks. The pandemic shifted our business model, so we are exploring maintaining a work-from-home model because this allows us to expand the amount of opportunity that we can provide to the communities in which we operate.

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AI Technology Can Enhance Human-Centered Work Instead Of Threaten It - Forbes