Daily Archives: April 9, 2020

Five investment strategies to mitigate systemic risks before the next pandemic – ImpactAlpha

Posted: April 9, 2020 at 6:16 pm

As we watch unemployment numbers rise and markets flounder, it is painfully clear how pandemics not only impact individuals health and well-being, but also devastate the entire global economy. The scope and scale of COVID-19 and its related economic fallout stem in large part from the fact that the worlds social and financial systems with their interconnected businesses and supply chains have become so intertwined and interdependent that a disruption to one can ramify, rapidly wreaking havoc for all.

Yet, most investors continue to operate on the assumption that they somehow operate separately from these systems and that systemic risks are beyond their control. We believe theyre wrong. We think individual investors and the financial system at large can and should invest and lend in ways that intentionally enhance, and not destroy, these systems.

Although finance cannot prevent the threat of the next pandemic, intentional system-level decision-making by investors and lenders can help us prepare for it more effectively and mitigate its worst societal and economic impacts. We need better guardrails. By taking a few decisive steps, we can help put these in place.

Heres what we need to do.

Allocate assets to the sovereign debt and municipal bond markets. Only local and national governments have the authority to take the draconian steps necessary to slow or stop pandemics. Investors need to invest in governments strong enough and with deep enough pockets to build guardrails and kindle economic recoveries. In addition, through the municipal bond market investors can support those non-profit hospitals that make up the vast majority of our acute care healthcare system and disproportionately serve low-income communities.

Many institutional investors, in search of yield today, have drastically cut their allocations to fixed income, chasing short-term returns by shifting assets to alternatives such as private equity and hedge funds. This is a short-sighted decision.

Investors should also stop investing in companies that dont pay their fair share of taxes and in financial services firms that promote tax avoidance services. What they are doing may not be illegal, but they are starving government of one of its most basic sources of revenues.

Insist that companies understand their business models and prepare backstops for their meltdown. Todays airline industry may never recover. Why? Because it did not understand that it is in the business of bringing people together: uniting families, convening businesses, solidifying friendships. If it had, it would have invested in Zoom or established its own telecommuting subsidiaries. Flight delayed? Stay at home or stop by our lounge and use our remote conferencing platform.

Todays fossil fuel companies, with few exceptions, lack the imagination for anything more than running out the clock on their current business models in as orderly a manner as possible, although decades ago some among their leaders had active renewable energy portfolios that they since opted to sell. At least the automobile and electric utility industries have an inkling that they should adapt to a future of alternative fuels.

Be willing to invest in firms that invest in the health of systems and prepare for potential systemic breakdowns. Excess manufacturing capacity may not be the most profitable way to run a business, but efficiency is not about letting people die because no one planned for ramping up ventilator production. The pursuit of efficiency has to stop short of abandoning all protection against disaster. If a firm makes belts, investors should ask whether they have a suspender line in the wings. Suspenders may be redundant and inefficient but its best not to be caught with your pants down.

Pharmaceutical companies that emphasize vaccines, generally a less profitable line of business than patented prescription drugs, deserve credit for understanding that prevention, particularly of pandemics, is part of their industrys mandate. A drugstore chain can remake itself into a full-service preventative healthcare provider. Invest in the system today or pay the price tomorrow.

The financial community thrives on lending. Debt is the most efficient way to boost the consumer economy. It works its magic for corporations too. Except when it cannot be repaid. We lent profligately to the housing market in the lead up to the 2008 financial crisis. Corporations loaded up on debt in the days before COVID-19 hit. The bonds of debt are excruciating to unwind; it can feel like forever; it can turn worlds upside down. The economic, social, and human costs of doing so destabilize.

The equivalent of belts and suspenders for lenders is the willingness to forgo a loan that is in fact too risky and to forgive those that cannot be repaid through no fault of borrowers. That means tough love to strengthen borrowers and lenders both. That strength will be needed to get through the next systemic crisis, pandemic or otherwise.

Being prepared means anticipating the worst, building in circuit breakers and guardrails, assuring redundancy and resilience, even when the worst seems unimaginable. Being prepared means investing in the health of fundamental systems.

We may be lucky and dodge the worst-case scenarios of the current fast-moving pandemic and the slow-motion train wreck that global warming will bring, but the 21st century will see other such systemic disruptions and we had better be ready for them.

William Burckart and Steve Lydenberg are the authors of the forthcoming book 21st Century Investing: Redirecting Financial Strategies to Drive Systems Change (Berrett-Koehler Publishers, 2021).

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Remaining Staff at The (Cleveland) Plain Dealer Prohibited from Covering Cleveland – Subscription Insider

Posted: at 6:15 pm

Wait, what? You read that headline correctly. Just daysafter The (Cleveland) Plain Dealer, Ohioslargest newspaper, laid off 22 newsroom employees, the remaining 14 employeesreceived more bad news. They have been prohibited from reporting on Cleveland,Cuyahoga County and Summit County, as well as any statewide news, reportsCleveScene.com. Those regions will now be covered by sister publication,Cleveland.com, a non-union shop. If the remaining newsroom employees want tokeep their jobs, they will be restricted to covering Geauga, Lake, Lorain,Medina and Portage Counties, other counties in northeast Ohio, instead of beatstheyve covered for years.

The Plain Dealer Newspaper Guild, representing the union, spokeout on Facebook on April 7 about this latest blow to a once-respected mediaoutlet. The post received 634 reactions, 274 comments and 770 shares, as of 8:30p.m. Eastern yesterday. Here is an excerpt:

The Plain Dealer newsroom will no longer be coveringCleveland, Cuyahoga County or the state of Ohio.

Editor Tim Warsinskey announced Monday to the 14 remainingstaff members that the newsroom would, with a few exceptions, become a bureaucovering five outlying counties: Geauga, Lake, Lorain, Medina and Portage.

The move would bar most of the reporters from coveringstories in Cuyahoga and Summit counties, as well as statewide issues, wherethey have developed expertise and have institutional knowledge.

This latest announcement comes as the newsroom has workedceaselessly in covering this unprecedented pandemic, putting aside their ownpersonal family and financial situations to cover the news and tell the storiesof health care workers and the community

Warsinskey called the move a company-wide strategydecision. He did not say which company.

The Plain Dealer, which is owned by Advance Publications,consistently has maintained that The Plain Dealer and Advance Local, areseparate companies. Advance Local operates the nonunion Cleveland.com newsroom,which has not announced layoffs.

The two-newsroom operation was never going to becometenable or permanent, Warsinskey told staffers.

In effect, he is admitting that this decision is part of abroader move to eliminate The Plain Dealer and its staff altogether and not anattempt to provide meaningful coverage on areas the company has stoppedreporting on in any depth for years. The announcement comes three days afterThe Plain Dealer laid off 22 people in the newsroom, including 18Guild-represented journalists and four nonunion managers.

Its clear that the company doesnt value the expertise ofits veteran reporters and it doesnt think the community does either, said thepost. Readthe complete post on Facebook.

In another interesting move, last night, there were nostories on The Plain Dealers website. There were scrolling photos, but noarticles. A Google search directed us to Cleveland.com/plaindealer,but there was no link to that site from PlainDealer.com that we could find.

It is not clear if this move was intentional, or perhaps atechnical glitch. It seems to foreshadow what is coming. Cleveland.com willtake over news reporting for what used to be the biggest paper in the state.Meanwhile, Cleveland.com looked like this. It contained Cleveland-based storieswith bylines from Cleveland.com reporters.

The Plain Dealers editor TimWarsinskey shared The Plain Dealers position with News 5 Cleveland on thechanges:

There are two separate, but related, newsrooms inCleveland, and two outstanding news products The Plain Dealer andcleveland.com. Together, they serve the market well with The Plain Dealerstories appearing online at cleveland.com and cleveland.com stories appearingin print in The Plain Dealer, an approach that has been in place since separatenewsrooms were established in 2013.

By design, this approach helps provide thoughtful, impactfulcoverage in the most efficient way possible and ensures that Greater Clevelandhas more access to local journalism via digital platforms as demand for thoseplatforms continues to grow.

Today, there are 77 journalists and content creators inthese newsrooms covering Greater Cleveland, doing outstanding reporting,writing stories and creating content that our readers want and deserve. Thisnumber is comparable to the staffs in similarly-sized metro areas in Ohio andacross the country. But its not just about the numbers of journalists we haveon hand. Its how they are deployed to create a broad base of coverage for allof the communities we serve in Greater Cleveland.

On Monday, The Plain Dealer shared a new reporting focuswith the members of its newsroom, one that offers to bring high quality localjournalism to five counties in Greater Cleveland, and the nearly 1 millionpeople who live in them. Lake, Geauga, Portage, Medina and Lorain counties havebeen underserved by media in this market for years despite making up a largepercentage of The Plain Dealers subscription base.

The Plain Dealer, along with our sister companyCleveland.com, has an opportunity to change that with The Plain Dealers newfocus on these five nearby counties. This broadening of our coverage area isespecially important in the midst of the COVID-19 pandemic, a time when all ofour readers, regardless of where they live, deserve to know how the virus isaffecting their local communities and how their local communities areresponding, Warsinskey said. Readthe full statement on News 5 Cleveland.

Cutting staff at a time when local journalism is more importantthan ever seems ludicrous, even if financially necessary. This latest move, however,makes absolutely no sense. Why would a media organization take skilledreporters with well-honed beats and move them to a bureau-type operation thatno longer reports news from the newspapers largest coverage area? It is almostunfathomable. We understand the guilds frustration and can only imagine how newspapersubscribers feel. It seems like Warsinskey and Advance Publications are notgiving the full story here. From the outside, it looks like they are cutting unionstaff and hoping the remaining staff will hate their plight so much that theywill leave voluntarily without a buyout or a mass firing. That would free thecompany up to transition to a digital model with non-union staff.

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‘Change the dynamics’: Dawoud Bey on photography, place, and history – 48 Hills

Posted: at 6:15 pm

On February 15, the San Francisco Museum of Modern Art opened An American Project, a retrospective, of the work of multi-award-winning photographer and teacher Dawoud Bey. The show was supposed to run through May 25, before traveling to other museums, including the co-organizer of the show, New Yorks Whitney Museum of American Art. But due to the COVID- 19 pandemic, the SFMOMA and other museums, closed temporarily in March. Recently the museum put up a short video of Bey talking about visualizing history, and he took over the museums Instagram account the week of March 30.

Bey came out to San Francisco for An American Project, and at a preview had a conversation with Corey Keller, (who curated the show along with the Whitneys Elisabeth Sherman), in which he talked about going to see protests of the widely criticized 1969 exhibit at the Metropolitan Museum of Art,Harlem on My Mind, which mostly excluded African American artists.There was no protest that day, and Bey ended up going into the show, which made him think seriously about being a photographer.

An American Project includes Beys first show, Harlem USA, along with The Birmingham Project, commemorating the 1963 dynamiting of the 16th Street Baptist Church in that city which killed four girls; Night Coming Tenderly, Blackabout the Underground Railroad; and Class Pictures, portraits of high school students accompanied by their words.

Bey sat down with 48 Hills and talked about changing from wanting his photos to show people in a positive light to just making honest photos; how for The Birmingham Project, photographing children the age of the ones who were killed makes history more specific; and the way the darkness and positioning of the photographs in Night Coming Tenderly, Blackpull viewers into the experience of being on the Underground Railroad and running for their lives.

48 HILLS Your godmother gave you a camera when you were 15. When did you start using it?

DAWOUD BEY When I got the camera, and it was a very basic Argus C3 Rangefinder camera, I had no idea how to use it. I was more fascinated by the camera itselfthe fact that the lens came off, and I began to figure out when you turn this dial the shutter would open slowly. I had no background in photography, and I didnt any think of it in terms of what would my subject matter be. So I just started walking around with this camera. I never made any memorable photos with that camera, but I did start to notice photography magazines like, Oh, theres actually magazines about this stuff. So it got me engaged with photography, and I started looking at photography books and magazines, and then the possibilities of what one might do with a camera opened up.

I guess the pivotal thing that happened was the following year when I was 16 and I went to see Harlem on my Mind at the Met. I actually took the camera with me, and I did take a picture of the banner in front of the Met.It was seeing that exhibition that began to expand for me considerably the notion of what the subject of photographs might be. Even though Harlem on My Mind was not an art exhibition, clearly the photographs were not that ones I saw in everyday newspapers and magazine, which up to that point was my only frame of reference for what photographs were.Seeing that exhibition and thinking about my familys history in Harlem, because my mother and father met in Harlem, and beginning to realize one has to have a kind of nominal subject around which to wrap their picture making, that allowed me to begin making photographs.

48H So that led to your first show, Harlem USA.

DB Yes. They were photographs of everyday people in Harlem in the public and semi public spaces of Harlem, largely in the streets, and a few in churches and in barber shops and greasy spoon luncheonette restaurants. Those were very much in the tradition of other pictures I had been looking ata lot from photographers of the WPA and Farm Security Administrator. Walker Evans became an early influence and Roy DeCarava.I started looking at the lot of photographs, trying to get a sense of how photos are made and what good photographs look like.

48H With that show, Harlem USA, what kind of photos did you want to make?

DB When I started out, I guess I wanted to make photographs that in some significant way contested the stereotypical notions of Black urban communities like Harlem, which are often described through a lens of some form of social pathology. So when I started out, I probably would have said I wanted to make photographs that represented the people of Harlem in a more positive light. But as I continued on, I couldnt quite figure out what a positive light looks like. This was merely people in the act of living their lives.

I eventually came to this notion of wanting to make an honest representation of everyday people in Harlem. It allowed me to let me let go of this binary notion of positive and negative, and just try and describe clearly the people in front of me without trying to put them in a box. Just allow them space to breathe, and I realized that was enough.

48H You have talked about showing your work in the communities where you took the photos and how the act of being seen is political.

DB I thought it was very important that the work I was making in that community be shown in that communitythat the people who were the subjects of the work would have access to the work. Certainly a number of these photographs are made in places very different from where theyre shown, but theyre first shown where they were made, from my first show at the Studio Museum in Harlem in 1979. It gave me a very clear and intentional way of thinking about the institution as a place of display. Not just the end point for the work, but to use the space of the museum to set up a series of particular relationships: between the museum and the community in which it sits, and trying to use the work in a way that a piece of community is in the work. It creates a different relationship between museum and the community, where they are aware theyre being exhibited in this space, which makes them more likely to want to have access to that space.

I think it changes the dynamics. Certainly at the Studio Museum in Harlem, its a very different set of circumstances because that place is set up in order to have a place for art objects within the African American community. I wanted my photographs in Harlem to extend that conversation. Usually the first showing of the work is in the place in which the work is made. The Birmingham Project was first shown in Birmingham because it has a very particular relationship with that history. The Class Pictures project was made in several different communities around the country, but each piece first shown in the city in which it was made.

48H Why did you decide to have the students you photographed in Class Pictures write something to go along with their portraits?

I thought it was necessary because I wanted a very dimensional representation of those young people. Im always acutely aware of the limitation of photographs because photographs dont do a lot more than they do. Theyre mute visual objects that present a particular piece of information. But all the information that lies out of the frame, which is a lot of information, tends not to be what the work is about.

In terms of making a contemporary portrait of young people in America, I thought it was important they not only be visualized in my photographs, but that they have a place of self representation and talk about their own lives in a way that the photograph is not capable of. That the two thingsmy portrait of them and the textcould add up to something more than either alone can represent. In that project I though it was really important to give them a literal voice in the construction of the image.

48H You talked about your work having a through line? What is it?

DB A sense of history and place. Theres always been a kind of close looking at a place. Photographs become history the moment that theyre made. They begin to recede into the past as soon as they are made. Its about bringing all of that into the conversation through my work. To have them become a part of the conversation from which theyve been largely excluded.

48H You said you went to Birmingham for years getting to know the city before deciding what you wanted to photograph to commemorate the bombing the 16th Street Baptist Church by white supremacists.How did you decide on young people the same age as the children who were killed in a diptych with someone who would have been their age if they lived?

DB I didnt want to just photograph young people in BirminghamI wanted them to be those specific ages. The girls were 11 and 14, and the two boys killed that afternoon were 13 and 16. I wanted them to be that age because for me, the work resonated more deeply in terms of what does an 11-year-old Black girl look like, because one of the girls who was killed in the dynamiting of the church was 11. Not just what does a young girl look like, but what does an 11-year-old African American girl look like.

Its a way of making that history less mythic and more specific.History as time passes tends to become very gauzy. The four little girls. It almost sounds like a girls singing group. Like what is that? I wanted to very specifically give you a sense of what a 14-year-old African American girl looks like, a 13-year-old African American boy. I want them to be that age as a way of invoking their presence in the work, not a presence, but their presence through those young people.And through the adults who were the same age they would have been if they had not been murdered.

48H The photos in your Underground Railroad series, Night Coming Tenderly, Black, are very dark. Why did you want them to look like that?

DB I wanted the viewer to think about moving through that landscape under cover of necessary darkness, as they moved, in that case, toward Lake Erie. I wanted to make photos that evoked that particular sensation. It kind of allowed the viewer to momentarily, through the photograph, inhabit that space under those circumstances, to imagine oneself moving though that terrain under threat of death.

The positionality of all of them is eye level and meant to be experienced as if one were the person moving through that landscape. I wanted it to be a heightened physical and psychological experience.

I had a very interesting experience at the Art Institute of Chicago when I showed them for the first time. I came into the gallery and two women had just finished looking at the work and they looked disoriented and they said to me, Youre the one who made these photographs, right? I said yes. But you made them now, right? Obviously you didnt go back, but why am I feeling Im someplace Im not? It kind of pulled them back. I really want the work to pull you into the experience, so its not just a space of the imagination, which it is, but that it resonates as experience.

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Stop calling coronavirus pandemic a ‘war’ – The Conversation UK

Posted: at 6:13 pm

In speeches, commentaries and conversations about the coronavirus pandemic, we keep hearing war-like metaphors being deployed. It happens explicitly (we are at war, blitz spirit, war cabinet) and implicitly (threat, invisible enemy, frontline, duty).

This, after all, helps project an interpretation of the extraordinary reality facing us which is readily understandable. It helps convey a sense of exceptional mobilisation and offers to decision-makers an opportunity to rise up as heroic commanders.

It is also true that the language of biomedicine and epidemiology is already heavily militarised. We battle a virus, and our body has defence mechanisms against the pathogens that invade it.

But the coronavirus crisis is an international, pan-human challenge. It certainly requires exceptional collective mobilisation, but no real weapons, no intentional killing of fellow human beings, and no casting of people as dehumanised others. Militarised language is unnecessary.

Explaining and encouraging community resilience and togetherness in the face of adversity by evoking images of war conjures up distorted myths and narratives of heroic past national glory and military campaigns. This might function as a cognitive shortcut to evoke collective effort, but the narrow narratives it reproduces are open to exploitation by opportunistic politicians.

We could just as much favour analysis of the evolving situation in calmer scientific and medical terms. You dont need ideas about war to tell a story of the human race naturally coming together when faced by a common danger.

Indeed, one striking phenomenon has been the huge proliferation of organic networks of mutual aid. From street-level up, and often with the help of social media, a huge number of people have been organising solidarity networks to help each other and especially the most vulnerable.

People have come together and organised within neighbourhoods, cities and regions but also across nations to help each other without needing to call it a war or military duty. The language of mutual aid and solidarity works just as well.

Anyone interested in political theory and ideologies must be watching all this with some intellectual curiosity. Different perspectives come with different assumptions about human nature, the role of the state compared to other institutions, and so on.

War is the business of the state par excellence. Some argue it was war-making that actually made the modern state. Framing the response to COVID-19 in military language will reinforce such statist thinking and the statist project itself. It will reinforce the state and its power.

It is of course true that, given the political architecture in place as the crisis hit, states do hold much organisational capacity and power. They have a crucial role to play in tackling the current emergency. But other political entities matter too, from spontaneous bottom-up networks and municipalities to regional organisations and the World Health Organization. Military metaphors, however, either conceal their contributions or co-opt them by describing their efforts in military terms.

One could just as much pitch the crisis as being about medicine, health workers and human communities across the globe. One could analyse events around particular socio-economic classes, such as supermarket workers, delivery workers and essential equipment manufacturers, in every country affected by the virus. Looking at socio-economic classes across borders could also set up more searching discussions about homelessness, refugee camps, working conditions and universal healthcare.

An analysis based on class or social justice is just as appropriate as one revolving around military metaphors. But instead of reinforcing statist and military thinking, it would explain the crisis in anarchist, Marxist, feminist, or liberal internationalist terms, for example.

Language matters. It helps frame particular stories, interpretations and conversations while at the same time closing off alternative perspectives. It reinforces particular theories about how the world works, and sidelines others.

Framing political issues in the language of war both illustrates the prevalence of militarised thinking and further enables it. The more we use military language, the more we normalise the mobilisation of the military and the more we entrench military hierarchies. When the next international crisis arrives, rather than examining the deeper structural problems that caused them, we jump again to heroic narratives of national militarised mobilisation.

Who benefits from this? Politicians can project an image of decisive generals protecting their lot. Agents of state coercion can project themselves as dutiful and robust but popular administrators of the public will. They can then mobilise this (typically masculine) brand for their own political agenda later on. If you are Trump, perhaps you can even egg up some anti-Chinese patriotism.

Missed is the opportunity to develop a more nuanced understanding of human capabilities not restricted to national boundaries. Yet this international solidarity and these pan-human capabilities might be what we need to tackle other problems of international scale, such as the climate crisis.

When a crisis of global proportions gives rise to organic expressions of mutual aid, our imagination has grown so restricted that we find ourselves framing the challenge in statist and national terms. Instead of seeing the whole of humanity rising to the challenge together and observing the multi-layered outpouring of mutual aid, our imagination is restricted into encasing this in military language.

But that does not capture the full story. The human race will come out of COVID wiser if it does not frame its understanding of its response to it in narrow military language.

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Campuses Might Still Be Closed in the Fall. How Should… – Diverse: Issues in Higher Education

Posted: at 6:13 pm

April 7, 2020 | :

After varying amounts of struggle, universities across the country moved online for the spring semester in response to the coronavirus pandemic. But now the question is, whats next?

While some hope campuses will re-open come fall, no one knows for certain. In the meantime, university leaders are girding themselves for the possibility theyll have to offer another semester online and asking themselves how to best prepare for more long-term remote learning.

Many are thinking outside the box and outside the (virtual) classroom about what resources students will need if online classes continue next year.

Over spring break, most campuses didnt have the time to build the highest quality online programs as they scurried to open their virtual doors, but fall may hold new possibilities.

Clare McCann, deputy director for federal higher education policy at the think tank New America, stressed the importance of not only intentional instructional design but online student support now that schools have a small (albeit very small) extra amount of time to prepare, she wrote in an email.

Dr. Alison Davis-Blake, president of Bentley University, is working to create a true virtual campus, not just online courses, she said, to offer as much of the campus experience as possible online.

For example, the school held an online career fair and continues to offer remote career counseling. Groups of 40 students virtually meet with a student affairs representative for weekly check-ins and coaches continue to touch base with their athletes, even though they cant play. Student government is up and running, alongside fraternities, sororities and other student groups that continue to virtually meet.

The university plans to look at student and faculty surveys this summer to assess its online education this spring, and most importantly, what could be improved in the fall if remote classes continue. The hope is to offer more experiential learning opportunities and to make more on-campus services remotely available.

But as Davis-Blake pointed out, an online fall semester would pose a new challenge: on-boarding a first-year class amidst the pandemic.

University leaders are asking themselves, How do you orient students when youre not face to face? she said. What can you do over the summer to bring students in?

Shes thinking through a number of options virtual tours, group chats for new students, or even small regional group gatherings, if theyre safe when the semester starts.

Preparing for the possibility of a fall semester online, its almost as if youre building a university from the ground up, Davis-Blake said. For colleges, the key is thinking about what is an important part of your campus experience? And [then] trying to bring that forward.

Its a question Dr. Wayne A.I. Frederick, president of Howard University, is contending with as well. The historically Black college (HBCU) is known for its family dynamic, he said, so hes considering what that means and what that looks like if students remain online in the fall.

The camaraderie students feel at an HBCU is difficult to create in a distance learning environment, he said. We do have to start thinking, What are our values, what are our traditions, and how do we uphold those in the middle of a crisis such as this?

For all universities, but particularly schools like Howard, which serve high percentages of low-income students, the possible continuation of online learning comes with another worry retention rates.

Frederick is concerned that students financially impacted by the coronavirus may not come back to campus next year, so continuing online options in the fall even if on-campus classes are safe might help students who need to work and might otherwise struggle to return, he said. In the meantime, part of the schools preparation for fall is carefully monitoring students and reaching out to those who may need help with their finances.

Frederick finds that the crisis, and the accompanying shift online, is impacting his students in diverse ways, with Black communities disproportionately affected by the coronavirus. Some need mentorship, others need devices to just to get online, and as a student survey found, many need quiet spaces to study at home.

So, as time goes on, he wants to continue tailoring services to their individual needs. For example, if places like libraries reopen before campuses next semester, Howard University might create a guide to finding safe, local study spots.

In preparing for the fall, we need to ask our students what they need rather than be proscriptive, he said.

Though everyone hopes for more normalcy in the next academic year, Davis-Blake thinks the process of making emergency plans for fall might actually help universities understand and address their students needs better. Campuses may find that some supports actually reach more students more effectively online, while others require an in-person touch.

I really believe this is a period not just to hunker down and say, Well, how do we get through? she said. This is a time for creativity. Even if we come back to campus and were all face to face, there are things were learning and will keep learning about how to deliver education even better through virtual and in-person activities. In every calamity, there is a possibility and an opportunity for innovation, for growth, for the human spirit to really rise.

Sara Weissman can be reached at sweissman@diverseeducation.com.

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AI and the coronavirus fight: How artificial intelligence is taking on COVID-19 – ZDNet

Posted: at 6:09 pm

As the COVID-19 coronavirus outbreak continues to spread across the globe, companies and researchers are looking to use artificial intelligence as a way of addressing the challenges of the virus. Here are just some of the projects using AI to address the coronavirus outbreak.

Using AI to find drugs that target the virus

A number of research projects are using AI to identify drugs that were developed to fight other diseases but which could now be repurposed to take on coronavirus. By studying the molecular setup of existing drugs with AI, companies want to identify which ones might disrupt the way COVID-19 works.

BenevolentAI, a London-based drug-discovery company, began turning its attentions towards the coronavirus problem in late January. The company's AI-powered knowledge graph can digest large volumes of scientific literature and biomedical research to find links between the genetic and biological properties of diseases and the composition and action of drugs.

EE: How to implement AI and machine learning (ZDNet special report) | Download the report as a PDF (TechRepublic)

The company had previously been focused on chronic disease, rather than infections, but was able to retool the system to work on COVID-19 by feeding it the latest research on the virus. "Because of the amount of data that's being produced about COVID-19 and the capabilities we have in being able to machine-read large amounts of documents at scale, we were able to adapt [the knowledge graph] so to take into account the kinds of concepts that are more important in biology, as well as the latest information about COVID-19 itself," says Olly Oechsle, lead software engineer at BenevolentAI.

While a large body of biomedical research has built up around chronic diseases over decades, COVID-19 only has a few months' worth of studies attached to it. But researchers can use the information that they have to track down other viruses with similar elements, see how they function, and then work out which drugs could be used to inhibit the virus.

"The infection process of COVID-19 was identified relatively early on. It was found that the virus binds to a particular protein on the surface of cells called ACE2. And what we could with do with our knowledge graph is to look at the processes surrounding that entry of the virus and its replication, rather than anything specific in COVID-19 itself. That allows us to look back a lot more at the literature that concerns different coronaviruses, including SARS, etc. and all of the kinds of biology that goes on in that process of viruses being taken in cells," Oechsle says.

The system suggested a number of compounds that could potentially have an effect on COVID-19 including, most promisingly, a drug called Baricitinib. The drug is already licensed to treat rheumatoid arthritis. The properties of Baricitinib mean that it could potentially slow down the process of the virus being taken up into cells and reduce its ability to infect lung cells. More research and human trials will be needed to see whether the drug has the effects AI predicts.

Shedding light on the structure of COVID-19

DeepMind, the AI arm of Google's parent company Alphabet, is using data on genomes to predict organisms' protein structure, potentially shedding light on which drugs could work against COVID-19.

DeepMind has released a deep-learning library calledAlphaFold, which uses neural networks to predict how the proteins that make up an organism curve or crinkle, based on their genome. Protein structures determine the shape of receptors in an organism's cells. Once you know what shape the receptor is, it becomes possible to work out which drugs could bind to them and disrupt vital processes within the cells: in the case of COVID-19, disrupting how it binds to human cells or slowing the rate it reproduces, for example.

Aftertraining up AlphaFold on large genomic datasets, which demonstrate the links between an organism's genome and how its proteins are shaped, DeepMind set AlphaFold to work on COVID-19's genome.

"We emphasise that these structure predictions have not been experimentally verified, but hope they may contribute to the scientific community's interrogation of how the virus functions, and serve as a hypothesis generation platform for future experimental work in developing therapeutics," DeepMind said. Or, to put it another way, DeepMind hasn't tested out AlphaFold's predictions outside of a computer, but it's putting the results out there in case researchers can use them to develop treatments for COVID-19.

Detecting the outbreak and spread of new diseases

Artificial-intelligence systems were thought to be among the first to detect that the coronavirus outbreak, back when it was still localised to the Chinese city of Wuhan, could become a full-on global pandemic.

It's thought that AI-driven HealthMap, which is affiliated with the Boston Children's Hospital,picked up the growing clusterof unexplained pneumonia cases shortly before human researchers, although it only ranked the outbreak's seriousness as 'medium'.

"We identified the earliest signs of the outbreak by mining in Chinese language and local news media -- WeChat, Weibo -- to highlight the fact that you could use these tools to basically uncover what's happening in a population," John Brownstein, professor of Harvard Medical School and chief innovation officer at Boston Children's Hospital, told the Stanford Institute for Human-Centered Artificial Intelligence's COVID-19 and AI virtual conference.

Human epidemiologists at ProMed, an infectious-disease-reporting group, published their own alert just half an hour after HealthMap, and Brownstein also acknowledged the importance of human virologists in studying the spread of the outbreak.

"What we quickly realised was that as much it's easy to scrape the web to create a really detailed line list of cases around the world, you need an army of people, it can't just be done through machine learning and webscraping," he said. HealthMap also drew on the expertise of researchers from universities across the world, using "official and unofficial sources" to feed into theline list.

The data generated by HealthMap has been made public, to be combed through by scientists and researchers looking for links between the disease and certain populations, as well as containment measures. The data has already been combined with data on human movements, gleaned from Baidu,to see how population mobility and control measuresaffected the spread of the virus in China.

HealthMap has continued to track the spread of coronavirus throughout the outbreak, visualising itsspread across the world by time and location.

Spotting signs of a COVID-19 infection in medical images

Canadian startup DarwinAI has developed a neural network that can screen X-rays for signs of COVID-19 infection. While using swabs from patients is the default for testing for coronavirus, analysing chest X-rays could offer an alternative to hospitals that don't have enough staff or testing kits to process all their patients quickly.

DarwinAI released COVID-Net as an open-source system, and "the response has just been overwhelming", says DarwinAI CEO Sheldon Fernandez. More datasets of X-rays were contributed to train the system, which has now learnt from over 17,000 images, while researchers from Indonesia, Turkey, India and other countries are all now working on COVID-19. "Once you put it out there, you have 100 eyes on it very quickly, and they'll very quickly give you some low-hanging fruit on ways to make it better," Fernandez said.

The company is now working on turning COVID-Net from a technical implementation to a system that can be used by healthcare workers. It's also now developing a neural network for risk-stratifying patients that have contracted COVID-19 as a way of separating those with the virus who might be better suited to recovering at home in self-isolation, and those who would be better coming into hospital.

Monitoring how the virus and lockdown is affecting mental health

Johannes Eichstaedt, assistant professor in Stanford University's department of psychology, has been examining Twitter posts to estimate how COVID-19, and the changes that it's brought to the way we live our lives, is affecting our mental health.

Using AI-driven text analysis, Eichstaedt queried over two million tweets hashtagged with COVID-related terms during February and March, and combined it with other datasets on relevant factors including the number of cases, deaths, demographics and more, to illuminate the virus' effects on mental health.

The analysis showed that much of the COVID-19-related chat in urban areas was centred on adapting to living with, and preventing the spread of, the infection. Rural areas discussed adapting far less, which the psychologist attributed to the relative prevalence of the disease in urban areas compared to rural, meaning those in the country have had less exposure to the disease and its consequences.

SEE:Coronavirus: Business and technology in a pandemic

There are also differences in how the young and old are discussing COVID-19. "In older counties across the US, there's talk about Trump and the economic impact, whereas in young counties, it's much more problem-focused coping; the one language cluster that stand out there is that in counties that are younger, people talk about washing their hands," Eichstaedt said.

"We really need to measure the wellbeing impact of COVID-19, and we very quickly need to think about scalable mental healthcare and now is the time to mobilise resources to make that happen," Eichstaedt told the Stanford virtual conference.

Forecasting how coronavirus cases and deaths will spread across cities and why

Google-owned machine-learning community Kaggle is setting a number of COVID-19-related challenges to its members, includingforecasting the number of cases and fatalities by cityas a way of identifying exactly why some places are hit worse than others.

"The goal here isn't to build another epidemiological model there are lots of good epidemiological models out there. Actually, the reason we have launched this challenge is to encourage our community to play with the data and try and pick apart the factors that are driving difference in transmission rates across cities," Kaggle's CEO Anthony Goldbloom told the Stanford conference.

Currently, the community is working on a dataset of infections in 163 countries from two months of this year to develop models and interrogate the data for factors that predict spread.

Most of the community's models have been producing feature-importance plots to show which elements may be contributing to the differences in cases and fatalities. So far, said Goldbloom, latitude and longitude are showing up as having a bearing on COVID-19 spread. The next generation of machine-learning-driven feature-importance plots will tease out the real reasons for geographical variances.

"It's not the country that is the reason that transmission rates are different in different countries; rather, it's the policies in that country, or it's the cultural norms around hugging and kissing, or it's the temperature. We expect that as people iterate on their models, they'll bring in more granular datasets and we'll start to see these variable-importance plots becoming much more interesting and starting to pick apart the most important factors driving differences in transmission rates across different cities. This is one to watch," Goldbloom added.

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You Cant Spell Creative Without A.I. – The New York Times

Posted: at 6:09 pm

This article is part of our latest Artificial Intelligence special report, which focuses on how the technology continues to evolve and affect our lives.

Steve Jobs once described personal computing as a bicycle for the mind.

His idea that computers can be used as intelligence amplifiers that offer an important boost for human creativity is now being given an immediate test in the face of the coronavirus.

In March, a group of artificial intelligence research groups and the National Library of Medicine announced that they had organized the worlds scientific research papers about the virus so the documents, more than 44,000 articles, could be explored in new ways using a machine-learning program designed to help scientists see patterns and find relationships to aid research.

This is a chance for artificial intelligence, said Oren Etzioni, the chief executive of the Allen Institute for Artificial Intelligence, a nonprofit research laboratory that was founded in 2014 by Paul Allen, the Microsoft co-founder.

There has long been a dream of using A.I. to help with scientific discovery, and now the question is, can we do that?

The new advances in software applications that process human language lie at the heart of a long-running debate over whether computer technologies such as artificial intelligence will enhance or even begin to substitute for human creativity.

The programs are in effect artificial intelligence Swiss Army knives that can be repurposed for a host of different practical applications, ranging from writing articles, books and poetry to composing music, language translation and scientific discovery.

In addition to raising questions about whether machines will be able to think creatively, the software has touched off a wave of experimentation and has also raised questions about new challenges to intellectual property laws and concerns about whether they might be misused for spam, disinformation and fraud.

The Allen Institute program, Semantic Scholar, began in 2015. It is an early example of this new class of software that uses machine-learning techniques to extract meaning from and identify connections between scientific papers, helping researchers more quickly gain in-depth understanding.

Since then, there has been a rapid set of advances based on new language process techniques leading a variety of technology firms and research groups to introduce competing programs known as language models, each more powerful than the next.

What has been in effect an A.I. arms race reached a high point in February, when Microsoft introduced Turing-NLG (natural language generation), named after the British mathematician and computing pioneer Alan Turing. The machine-learning behemoth consists of 17 billion parameters, or weights, which are numbers that are arrived at after the program was trained on an immense library of human-written texts, effectively more than all the written material available on the internet.

As a result, significant claims have been made for the capability of language models, including the ability to write plausible-sounding sentences and paragraphs, as well as draw and paint and hold a believable conversation with a human.

Where weve seen the most interesting applications has really been in the creative space, said Ashley Pilipiszyn, a technical director at OpenAI, an independent research group based in San Francisco that was founded as a nonprofit research organization to develop socially beneficial artificial intelligence-based technology and later established a for-profit corporation.

Early last year, the group announced a language model called GPT-2 (generative pretrained transformer), but initially did not release it publicly, saying it was concerned about potential misuse in creating disinformation. But near the end of the year, the program was made widely available.

Everyone has innate creative capabilities, she said, and this is a tool that helps push those boundaries even further.

Hector Postigo, an associate professor at the Klein College of Media and Communication at Temple University, began experimenting with GPT-2 shortly after it was released. His first idea was to train the program to automatically write a simple policy statement about ethics policies for A.I. systems.

After fine-tuning GPT-2 with a large collection of human-written articles, position papers, and laws collected in 2019 on A.I., big data and algorithms, he seeded the program with a single sentence: Algorithmic decision-making can pose dangers to human rights.

The program created a short essay that began, Decision systems that assume predictability about human behavior can be prone to error. These are the errors of a data-driven society. It concluded, Recognizing these issues will ensure that we are able to use the tools that humanity has entrusted to us to address the most pressing rights and security challenges of our time.

Mr. Postigo said the new generation of tools would transform the way people create as authors.

We already use autocomplete all the time, he said. The cat is already out of the bag.

Since his first experiment, he has trained GPT-2 to compose classical music and write poetry and rap lyrics.

That poses the question of whether the programs are genuinely creative. And if they are able to create works of art that are indistinguishable from human works, will they devalue those created by humans?

A.I. researchers who have worked in the field for decades said that it was important to realize that the programs were simply assistive and that they were not creating artistic works or making other intellectual achievements independently.

The early signs are that the new tools will be quickly embraced. The Semantic Scholar coronavirus webpage was viewed more than 100,000 times in the first three days it was available, Dr. Etzioni said. Researchers at Google Health, Johns Hopkins University, the Mayo Clinic, the University of Notre Dame, Hewlett Packard Labs and IBM Research are using the service, among others.

Jerry Kaplan, an artificial-intelligence researcher who was involved with two of Silicon Valleys first A.I. companies, Symantec and Teknowledge during the 1980s, pointed out that the new language modeling software was actually just a new type of database retrieval technology, rather than an advance toward any kind of thinking machine.

Creativity is still entirely on the human side, he said. All this particular tool is doing is making it possible to get insights that would otherwise take years of study.

Although that may be true, philosophers have begun to wonder whether these new tools will permanently change human creativity.

Brian Smith, a philosopher and a professor of artificial intelligence at the University of Toronto, noted that although students are still taught how to do long division by hand, calculators now are universally used for the task.

We once used rooms full of human computers to do these tasks manually, he said, noting that nobody would want to return to that era.

In the future, however, it is possible that these new tools will begin to take over much of what we consider creative tasks such as writing, composing and other artistic ventures.

What we have to decide is, what is at the heart of our humanity that is worth preserving, he said.

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Banking and payments predictions 2020: Artificial intelligence – Verdict

Posted: at 6:09 pm

Artificial intelligence (AI) refers to software-based systems that use data inputs to make decisions on their own. Machine learning is an application of AI that gives computer systems the ability to learn and improve from data without being explicitly programmed.

2019 saw financial institutions explore a broad-range of possible AI use cases in both customer-facing and back-office processes, increasing budgets, headcounts, and partnerships. 2020 will see increased focus on breaking out the marketing story from actual business impact to place bigger bets in fewer areas. This will help banks scale proven AI across the enterprise to forge competitive advantage.

Artificial intelligence will re-invigorate digital money management, helping incumbents drip-feed highly personalised spending tips to build trust and engagement in the absence of in-person interaction. Features like predictive insights around cashflow shortfalls, alerts on upcoming bill payments, and various what if scenarios when trying on different financial products give customers transparency around their options and the risks they face. This service will render as an always-on, in-your-pocket, and predictive advisor.

AI-enhanced customer relationship management (CRM) will help digital banks optimise product recommendations to rival the conversion rates of best-in-class online retailers. These product suggestions wont render as sales, but rather valuable advice received, such as a pre-approved loan before a cash shortfall or an option to remortgage to fund home improvements. This will help incumbents build customer advocacy and trust as new entrants vie for attention.

AI-powered onboarding, when combined with voice and facial recognition technologies, will help incumbents make themselves much easier to do business with, especially at the initial point of conversion but also thereafter at each moment of authentication. AI will offer particular support through Know Your Customer (KYC) processes, helping incumbents keep pace with new entrants. Standard Bank in South Africa, for example, used WorkFusions AI capabilities to reduce the customer onboarding time from 20 days to just five minutes.

Banks heavy compliance burden will continue to drive AI. Last year, large global banks such as OCBC Bank, Commonwealth Bank, Wells Fargo, and HSBC made big investments in areas such as automated data management, reporting, anti-money laundering (AML), compliance, automated regulation interpretation, and mapping. Increasingly partnering with artificial intelligence-enabled regtech firms will help incumbents reduce operational risk and enhance reporting quality.

As artificial intelligence becomes more embedded into all areas of customers lives, concerns around the black box driving decisions will grow, with more demands for explainable AI. As it is, customers with little or no digital footprint are less visible to applications that rely on data to profile people and assess risk. Traditional banks credit risk algorithms often disproportionately exclude black and Hispanic groups in the US as well as women, because these groups have historically earned less over their lifetimes.

In 2020, senior management will be held directly accountable for the decisions of AI-enabled algorithms. This will drive increased focus on data quality to feed the algorithms and perhaps limits to the use of the most dynamic machine learning because of their regulatory opacity.

This is an edited extract from the Banking & Payments Predictions 2020 Thematic Research report produced by GlobalData Thematic Research.

GlobalData is this websites parent business intelligence company.

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CORRECTION – Labelbox Awarded Artificial Intelligence Contract by Department of Defense – Yahoo Finance

Posted: at 6:09 pm

Leading provider of training data platforms for machine learning, Labelbox receives prestigious SBIR contract from AFWERX for U.S. Air Force

SAN FRANCISCO, April 09, 2020 (GLOBE NEWSWIRE) -- This release for Labelbox corrects and replaces the release issued today at 7:00 am ET with the headline Labelbox Awarded Artificial Intelligence Grant by Department of Defense. The word grant has been replaced in the headline, subheadline, and release body with the word contract. The corrected release follows.

Labelbox, the worlds leading training data platform, is among an elite selection of artificial intelligence companies to receive a contract from the Department of Defense to support national security as the U.S. scrambles to stay ahead of its rivals.

While some in Silicon Valley balk at working with the government, Labelboxs founders are vocal about their belief that technology companies have a responsibility to help the U.S. maintain its technological advantage in the face of competition from nation states.

I grew up in a poor family, with limited opportunities and little infrastructure said Manu Sharma, CEO and one of Labelboxs co-founders, who was raised in a village in India near the Himalayas. He said that opportunities afforded by the U.S. have helped him achieve more success in ten years than multiple generations of his family back home. Weve made a principled decision to work with the government and support the American system, he said.

Labelbox is a software platform that allows data science teams to manage the data used to train supervised-learning models. Supervised learning is a branch of artificial intelligence that uses labeled data to train algorithms to recognize patterns in images, audio, video or text. After being fed millions of labeled pictures of mobile missile launchers from satellite imagery, for example, a supervised-learning system will learn to pick out missile launchers in pictures it has never seen.

For data science teams to work better with each other and with labelers around the world, they need a platform and tools. Without those things, managing large sets of data quickly becomes overwhelming. Labelbox solves that problem by facilitating collaboration, rework, quality assurance, model evaluation, audit trails, and model-assisted labeling in one platform. The platform is tailored for computer vision systems but can handle all forms of data. The platform also helps with billing and time management.

Labelbox is an integrated solution for data science teams to not only create the training data but also to manage it in one place, said Sharma. Its the foundational infrastructure for customers to build their machine learning pipeline.

The company won an Air Force AEFWRX Phase 1 Small Business Innovation Research contract to conduct feasibility studies on how to integrate the Labelbox platform with various stakeholders in the Air Force. Labelbox recently hired a representative in Washington, D.C., to manage the process.

The Small Business Innovation Research (SBIR) program is a highly competitive program that encourages domestic small businesses to engage in Federal Research and Development. The United States Department of Defense is the largest of 11 federal agencies participating in the program. Air Force Innovation Hub Network (AFWERX) is a United States Air Force program intended to engage innovators and entrepreneurs in developing effective solutions to challenges faced by the service.

About LabelboxFounded in 2018 and based in San Francisco, Labelbox is a collaborative training data platform for machine learning applications. Instead of building their own expensive and incomplete homegrown tools, companies rely on Labelbox as the training data platform that acts as a central hub for data science teams to interface with dispersed labeling teams. Better ways to input and manage data translates into higher-quality training data and more accurate machine-learning models. Labelbox has raised $39 million in capital from leading VCs in Silicon Valley. For more information, visit: https://www.Labelbox.com/

Editorial ContactLonn Johnston for Labelbox+1 650.219.7764lonn@flak42.com

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Global Artificial Intelligence in Supply Chain Market (2020 to 2027) – by Component Technology, Application and by End User – ResearchAndMarkets.com -…

Posted: at 6:08 pm

The "Artificial Intelligence in Supply Chain Market by Component (Platforms, Solutions) Technology (Machine Learning, Computer Vision, Natural Language Processing), Application (Warehouse, Fleet, Inventory Management), and by End User - Global Forecast to 2027" report has been added to ResearchAndMarkets.com's offering.

This report carries out an impact analysis of the key industry drivers, restraints, challenges, and opportunities. Adoption of artificial intelligence in the supply chain allows industries to track their operations, enhance supply chain management productivity, augment business strategies, and engage with customers in the digital world.

The growth of artificial intelligence in supply chain market is driven by several factors such as raising awareness of artificial intelligence and big data & analytics and widening implementation of computer vision in both autonomous & semi-autonomous applications. Moreover, the factors such as consistent technological advancements in the supply chain industry, rising demand for AI-based business automation solutions, and evolving supply chain automation are also contributing to the market growth.

The overall AI in supply chain market is segmented by component (hardware, software, and services), by technology (machine learning, computer vision, natural language processing, cognitive computing, and context-aware computing), by application (supply chain planning, warehouse management, fleet management, virtual assistant, risk management, inventory management, and planning & logistics), and by end-user (manufacturing, food and beverages, healthcare, automotive, aerospace, retail, and consumer-packaged goods), and geography.

Companies Mentioned

Key Topics Covered:

1. Introduction

2. Research Methodology

3. Executive Summary

3.1. Overview

3.2. Market Analysis, by Component

3.3. Market Analysis, by Technology

3.4. Market Analysis, by Application

3.5. Market Analysis, by End User

3.6. Market Analysis, by Geography

3.7. Competitive Analysis

4. Market Insights

4.1. Introduction

4.2. Market Dynamics

4.2.1. Drivers

4.2.1.1. Rising Awareness of Artificial Intelligence and Big Data & Analytics

4.2.1.2. Widening Implementation of Computer Vision in both Autonomous & Semi-Autonomous Applications

4.2.2. Restraints

4.2.2.1. High Procurement and Operating Cost

4.2.2.2. Lack of Infrastructure

4.2.3. Opportunities

4.2.3.1. Growing Demand for AI -Based Business Automation Solutions

4.2.3.2. Evolving Supply Chain Automation

4.2.4. Challenges

4.2.4.1. Data Integration from Multiple Resources

4.2.4.2. Concerns Over Data Privacy

4.2.5. Trends

4.2.5.1. Rising Adoption of 5g Technology

4.2.5.2. Rising Demand for Cloud-Based Supply Chain Solutions

5. Artificial Intelligence in Supply Chain Market, by Component

5.1. Introduction

5.2. Software

5.2.1. AI Platforms

5.2.2. AI Solutions

5.3. Services

5.3.1. Deployment & Integration

5.3.2. Support & Maintenance

5.4. Hardware

5.4.1. Networking

5.4.2. Memory

5.4.3. Processors

6. Artificial Intelligence in Supply Chain Market, by Technology

6.1. Introduction

6.2. Machine Learning

6.3. Natural Language Processing (NLP)

6.4. Computer Vision

6.5. Context-Aware Computing

7. Artificial Intelligence in Supply Chain Market, by Application

7.1. Introduction

7.2. Supply Chain Planning

7.3. Virtual Assistant

7.4. Risk Management

7.5. Inventory Management

7.6. Warehouse Management

7.7. Fleet Management

7.8. Planning & Logistics

8. Artificial Intelligence in Supply Chain Market, by End User

8.1. Introduction

8.2. Retail Sector

8.3. Manufacturing Sector

8.4. Automotive Sector

8.5. Aerospace Sector

8.6. Food & Beverage Sector

8.7. Consumer Packaged Goods Sector

8.8. Healthcare Sector

9. Global Artificial Intelligence in Supply Chain Market, by Geography

9.1. Introduction

9.2. North America

9.2.1. U.S.

9.2.2. Canada

9.3. Europe

9.3.1. Germany

9.3.2. U.K.

9.3.3. France

9.3.4. Spain

9.3.5. Italy

9.3.6. Rest of Europe

9.4. Asia-Pacific

9.4.1. China

9.4.2. Japan

9.4.3. India

9.4.4. Rest of Asia-Pacific

9.5. Latin America

9.6. Middle East & Africa

10. Competitive Landscape

10.1. Key Growth Strategies

10.2. Competitive Developments

10.2.1. New Product Launches and Upgradations

10.2.2. Mergers and Acquisitions

10.2.3. Partnerships, Agreements, & Collaborations

10.2.4. Expansions

10.3. Market Share Analysis

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