Daily Archives: October 4, 2022

Gambling Addiction – Signs, symptoms, risks and treatment – recovered

Posted: October 4, 2022 at 1:21 pm

Gambling addiction is currently the only form of behavioral addiction recognized by the American Psychiatric Association. As outlined in The Diagnostic and Statistical Manual of Mental Disorders, 5th edition (DSM-5), gambling addiction can be diagnosed using the 11 criteria for measuring substance addiction, but what is it?

Gambling is a diverse activity that is not designated solely to casinos and card games. Many forms of gambling occur in day-to-day life, including buying lottery tickets, poker games, online gambling, legalized gambling, or placing bets on sports games. For many, these activities are casual and infrequent and dont threaten their financial security. However, for others, gambling is a much more frequent and problematic behavior that causes them to lose control and experience devastating financial losses.

Like many forms of substance abuse, gambling activates the reward center in the brain and causes the release of dopamine. Pathological gamblers will feel a rush when placing a bet, and may even have a bigger rush when placing large or risky bets. People with a gambling disorder become fixated, building their routine around either chasing the high from winning with increasingly risky bets or desperately trying to recoup their losses. It can be a devastating cycle, one which leaves many in financial ruin and emotional turmoil every year. [1][2]

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Genetics, psychological make-up, a persons environment, and past trauma can all make a person more vulnerable to addictions, including gambling disorder. Outside of the recognized causes of addiction, someone may also become a compulsive gambler if they are in difficult financial circumstances as a means of getting out of them. Others may develop an addiction after experiencing the rush of a lucky bet or winning streak. Others may simply enjoy the perceived lifestyle of gambling and may not be aware of how it is damaging their lives.

Compulsive disorders and addictive disorders are closely linked but are categorized differently in the DSM 5 (the reference guide used to diagnose all mental illnesses and addictive disorders). The main difference between these disorders is that compulsions are impulsive patterns of behavior that cause negative consequences and problems, but dont necessarily cause the person to become physically or psychologically addicted.[1][2]

Addictive disorders like gambling disorder are known to cause the formation of addiction pathways in the brain which make it hard (but not impossible) for a person to control, cut back, or stop the behavior. Compulsive behaviors may be driven by fear, distress, or other impulses, as is the case in people with OCD who compulsively wash their hands or check their locks. They arent addicted to these behaviors but instead do them compulsively to alleviate their anxiety.

Gambling disorder is characterized by a pattern of compulsive gambling that becomes problematic and leads to the experience of negative consequences in an individuals life. Symptoms of gambling disorder include the experience of at least four of the following: [2]

A need to gamble with increasing amounts of money to achieve the same level of excitement or rush

Repeated unsuccessful efforts to stop or cut back on gambling

Restlessness or irritability when trying to cut back or stop gambling

Persistent preoccupation, or having frequent thoughts about gambling

A pattern of gambling when emotional or under stress

Returning to gambling after losing to recover losses

Lying to others or minimizing the extent of the gambling behavior

Risking or experiencing the loss of a significant relationship, job, or opportunity because of gambling

Relying on others to provide money to relieve financial strain caused by gambling

Some additional signs that can indicate someone has a Gambling Disorder or is at risk for developing one include:[2]

Spending more time or money gambling than you originally intended

Feelings of regret, remorse, or guilt after gambling

Gambling money that you cannot afford to lose

Intending, planning, or attempting to stop gambling but not following through

Feeling unable to control yourself when you start gambling

If you notice these signs or symptoms, it may mean that you are struggling with a gambling disorder, or that you are at risk of developing one.

Some who fall into patterns of excessive gambling may begin to display mental health issues such as depression and anxiety. This coupled with heavy losses can drive some to suicidal thoughts and actions.

One of the biggest indicators that addiction has formed is the inability to stop. If the thought of quitting gambling makes you anxious or you take active steps to carry on gambling, regardless of whether you are hurting yourself or others, then you likely have an addiction.

Unpaid debts that threaten financial, job, or personal security

Financial difficulties including debt or bankruptcy

Neglecting work and other responsibilities

Secretive behavior attempting to hide or conceal the problem

Mental health issues such as anxiety and depression or mood swings

Abusing substances to cope with psychological pressure from gambling, leading to drug and alcohol addictions

If you feel that you may be starting to develop a problem with gambling or have lost control, consider taking one or more of the following actions: [4]

Admit the scope of the problem and face it directly by calculating your losses and debts, and considering the amount of time and money spent on gambling

Recognize the negative effects gambling has had on you, loved ones, your life, and financial security

Find someone to talk to about the problem. Sharing your concerns with a loved one, therapist, or support group can help explore your feelings around the issue

Avoid locations and situations where you may be tempted to gamble and put safeguards in place that make it harder to give in to urges to gamble (i.e. leaving cash or credit cards at home or deleting apps used to gamble)

Visit our 12 tips to stop gambling page for more advice on how to reduce gambling.

Behavioral problems such as gambling addictions cannot be directly treated with medication, but medication may be needed to treat underlying or related conditions or symptoms like anxiety, mood swings, or depression. As there is no medication treatment for gambling addiction, many try to self-medicate. This can not only exacerbate any co-occurring conditions but also increases the risk of developing a secondary addiction to drugs or alcohol.

As with all types of addiction, loving someone who has a problem can be very difficult. Gambling addiction can put a huge strain on any relationship, especially if you share finances or have lent money to the person with the addiction.

If you think your partner or loved one may have the signs of being a problem gambler but you are unsure, ask yourself:

Do they promise time and time again to stop gambling but carry on anyway?

Do they disappear for long periods of time without telling you where they were?

Do they spend large sums of money without being able to account for it?

Do you hide money to stop them from spending it?

Do they lie to cover up or deny their gambling?

If you answered yes to one or more of these questions, here are some recommended steps to take: [4]

Have an open conversation with your loved one sharing your concerns

Set hard limits and boundaries about not lending them money

Limit access to shared accounts to protect financial assets

Encourage your loved one to get professional treatment

Consider a support group or counseling if you need additional help

If you or someone you care about is suffering from a gambling addiction, contact a treatment center today.

Gambling disorder is a treatable addiction, and many addiction centers have the ability to help people overcome this issue. Also, all states have free support and help (including counseling and support groups such as Gamblers Anonymous) for people struggling with gambling disorder. With treatment, its possible to overcome a gambling problem and regain control of your life and finances.

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Gambling Addiction - Signs, symptoms, risks and treatment - recovered

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14 Types of Gambling Games (2022 List)

Posted: at 1:21 pm

One of my favorite ways to learn about a new subject is to look at the various subdivisions of that subject. For example, Im writing a blog about gambling, so that leads me to wonder what the different types of gambling games are. If I were writing a blog about literature, I might look at how literature experts categorize that subject.

Ill start by offering a definition of gambling, and Ill follow that with a definition of game:

My favorite online dictionary, Merriam Webster, says that the word gamble has 2 definitions:

I saw an interesting discussion in the Wikipedia article about poker that relates to this, in fact. A well-meaning editor had removed the phrase gambling game from the pages lede, claiming that poker was a game of skill, not chance, and therefore it wasnt a gambling game.

But according to the definition from Merriam Webster, poker qualifies for sure. After all, youre playing a game for money. And the outcome of an individual hand in poker is uncertain, even when the odds are in your favor.

The legal definition of gambling might be another matter. USLegal.com has a page about the legal definition of gambling, and its also illuminating:

The legal definition agrees that risking money on an uncertain outcome is gambling, but it seems to make an exception for something thats not under a persons control or influence. This leads me to believe that a bet on a sporting contest that youre involved in wouldnt constitute gamblingat least not in a legal sense. Playing a game of billiards, darts, or golf (just to name 3 examples) for $20 with your drinking buddy wouldnt count.

That site also specifies that buying securities or commodities doesnt constitute gambling, even though the future price of those securities or commodities might be uncertain. In fact, anything that would qualify as a bona fide business transaction would be considered not gambling.

That seems to be a reasonably complete coverage of the definition of the word gambling, at least for this posts purpose.

Now whats a game?

Merriam-Websters definition of game is lengthier than its definition of gambling. The main definition is simple enough, though:

A game is any activity youre participating in for purposes of fun or diversion. The concept of competition is mentioned in one of the other definitions, too.

In fact, poker and other gambling games is the 1st example of the word used in a sentence in that definition.

The Wikipedia defines a game as a structured form of play. The page goes on to list some key components of an activity that constitutes a game:

I think most of these components apply to almost any gambling activity you can think of.

Whats your goal playing a slot machine?

You try to get certain symbols lined up on a pay line.

Blackjack has specific rules about what values the playing cards have.

The challenge in any gambling game is to win more money than you lose.

And youre interacting with someone or something every time you place a bet.

Im a simple man. I use simple strategies to find the information I want. To find categories of gambling games, I started with a Google search.

And one of the first pages I found included a great set of broad categories for gambling games:

Gambling games consisting of pure chance include keno and roulette. No amount of skill gives you influence over the results of a keno draw or a spin of the roulette wheel.

Craps is a game thats mostly about chance. You need some skill at choosing the right bets, though. The odds change dramatically from the basics bets to the proposition bets. And some players believe in dice setting or dice control.

Blackjack and poker are games of mostly skill. How you play your cards has a big role in determining your outcome. Card counters get an edge against the house. Skilled poker players also operate with a mathematical advantage.

But thats not the only way to categorize gambling games.

The California Council of Problem Gambling has the following gambling games list:

I disagree with some of their categorizations, but here are some insights into each category:

Casino card games include games like blackjack and Texas holdem. I wouldnt include traditional poker as as casino-style game, though. Poker games played against other players are dramatically different from games played in the casino proper.

Heres why:

In a real poker game, youre competing with the other players for money. In a casino card game, youre competing with the house for money. If you lose a hand of blackjack, the casino wins your money. If you lose a hand of poker, the other player at the table wins your money.

The house does bank some poker games, though.Caribbean Stud, for example, is a game you play in a casino versus the dealer. The actions of the other players at the table have no effect on your outcome.

The California Council on Problem Gamblings page lists some of the following card games as examples of other card games:

Id agree with their categorization, but Id include all poker games played against other players in this category instead of the casino card games category.

Any gambling game using dice to determine outcomes qualifies. Craps is the obvious example. Sic Bo is another, less well-known example. You could even gamble on Yahtzee if you wanted to.

The site lists the following games as examples:

It seems as if the California problem gambling site considers any game played on the internet to be an electronic gambling game, and I get that. Id probably include slot machines and video poker games played in brick and mortar casinos, though. That would also include the less common games, video blackjack and video roulette.

This is where you bet on the outcome of a sporting event that youre not participating in. Place a bet on a baseball or football game, and youre a sports bettor.

Sports betting is one of the more legally suspect gambling activities on this list. The Wire Act is a federal law that prohibits the running of a sports betting operation over the phone. For purposes of the law, this includes placing bets over the internet.

But the law only applies to the party taking the action. Placing the bet isnt a crime. Taking the bet is.

Companies (or individuals) who take sports bets as a business are called sports books. Theyre also sometimes just called books or bookies.

You can bet on sports with multiple offshore companies, even if you live in the United States. The companies accepting those bets can get in a lot of trouble if they get caught. Youre pretty safe, legally, though.

Betting on sports can be one of the most profitable betting games for the skilled bettor.

They dont have to be quarters. In fact, the Wikipedia article calls it pitching pennies. The concept is the same, though:

You throw a coin at the wall. So do your competitors. The person whose coin lands closest to the wall wins the coins.

Its an ancient game. Ive never thought of it when I wrote about gambling games lists before, though.

I doubt theres a lot of action in the quarter pitching market segment anymore. I do remember seeingThe Purple Rose of Cairo, and Danny Aiellos character was pitching pennies in that movie.

Lotteries have become ubiquitous in the United States. I think only 2 or 3 states have no lottery at the time of this writing.

Even when lotteries werent commonplace, private individuals ran lottery style games. These are the gangsters you hear about in the movies who are running numbers.

A number running game might work like this:

You pick 3 numbers between 0 and 9. The next day, the last 3 digits of the Dow Jones Industrial Average determine the winner. The individual running the numbers keeps a cut, of course.

But probably not as big a cut as the states who are running the lotteries keep. The mathematical expectation for these games is 50 cents on the dollar.

If you started with $1 million, bought a million lottery tickets with the money, and kept reinvesting your winnings, youd go broke much faster than you think:

Youd go broke in 3 weeks.

My best advice about gambling?

Skip the lottery altogethereven the seemingly-harmless scratch-off tickets.

I dont usually think of a raffle as a gambling game. But I guess it qualifies.

A raffle is when an organization wants to raise some money for some purpose. They offer some kind of prize, and they sell tickets for a drawing to win that prize.

Raffles resemble lotteries, but theyre privately held. Depending where you live, a raffle might be illegal.

Bingo resembles keno, lottery, and raffle games. The difference is the shape and makeup of the card. In the United States, a bingo card is a 5X5 grid. The word BINGO is printed across the top. The numbers are in the 25 squares.

Depending on the game, you win money based on getting a straight line or some other shape.

Bingo is the most socially accepted type of gambling in the world. Churches often host bingo games on a regular basis. People play bingo in elementary schools and nursing homes, although the prizes might not be cash.

But bingo isnt legal in every jurisdiction, either.

I discussed this category earlier. These are personal games of skill, like darts or billiards. I played in a weekly shuffleboard tournament at my local bar for 10 years. You paid $10 to play. You drew your partner at random.

The winners got the prize pool, and 2nd place got to play in the next weeks tournament free.

And if you dont think shuffleboard is a game of skill, let me tell you this:

I didnt win a tournament, no matter how strong a partner I had, for the 1st 9 years I participated.

The California site mentions Native American stick games and Mahjong as examples. I know that in some Middle Eastern countries, its common to bet on kite fighting. Participants create kites with blades on them and try to take out their opponents kites.

This is an odd category. It seems like all gambling games are cultural games for someone.

Around 91% of Americans use the internet in one form or another. One could assume that almost all of the gambling games listed above would have an online counterpart. The few gambling games I could see as outliers would be maybe kite fighting.

More and more states are legalizing online gambling and with that comes more options for playing gambling games online. You can even consider raffles online as well.

My daughter is a big Instagram user. She enters giveaways all the time, which could be considered a raffle of sorts. Shes trading her contact info and social media exposure for a chance to win a companys product in return. Money might not be exchanging hands but free social media exposure for an up and coming clothing brand is worth its weight in gold on Instagram, or just about any other social platform.

Online gambling is having a shining moment with the pandemic that shook the world in Marhc 2020. Everyone was at home and on the internet, ALL THE TIME. The traditional casinos closed. This left a huge open market for online gambling to step in and fill that void.

You can play just about any gambling online these days. fans of slot machines table games have 1000s of apps and website choices.

Are you a sports fan?

More than a dozen states have legalized online sports betting and daily fantasy sports leagues like DraftKings.com. Online sports betting is big business for sports teams and the online gambling arena. Just make sure you check your local laws to make sure its legal in your location.

The choices are almost unlimited when you look at online gambling games. If you like a certain gambling game, I promise theres most likely an online version of it.

This may seem like a redundant topic to include on this gambling game list but I think its an important one that we shouldnt overlook. Just about any gambling game can be replicated online (legal or not) with the right app or technology.

These are just examples of the types of gambling games you might consider playing. I used 2 different websites opinions about how they should be categorized. But I had problems with both their categorization schemes.

I could create lists of games where your decisions matter versus games where your decisions dont matter. I could also list games that use spinning wheels, like roulette or Wheel of Fortune. (Dont confuse that 2nd one with the popular TV game show.)

Ive done some work on a previous post that hopes to eventually be the most complete list of casino games on the internet. Ill probably return to that post soon to update it. I doubt it will ever be finished, though. Gambling game creators are hard at work looking for new and exciting ways to separate you from your money all the time.

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14 Types of Gambling Games (2022 List)

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Best 3 Online Gambling for Real Money Sites

Posted: at 1:21 pm

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Boston College Football vs. Clemson: Gambling Odds and Prediction – BC Interruption

Posted: at 1:21 pm

Well, last week was quite the ride for the Boston College football team as they were able to squeak by Louisville to secure their first ACC win of the season with a 34-33 win.

Like a responsible gambler, I stayed the hell away from this one and boy was that the right decision. The ending results of the match was a gamblers worst nightmare as the Eagles were able to cover the 15.5 spread, obviously, and absolutely destroy the Over of 51 which I originally guessed was set a tad bit too high.

Nonethless, not betting on the game allowed me to simply watch the game as a true fan and Alum and enjoy the spoils of victory.

A few quick observations going forward: The run game looked significantly improved, the O-line looked surprisingly improved (?) despite there being an additional lineman added to the injury report prior to kick-off, and Big Play Zay is practically unstoppable.

Now, moving forward, the Eagles will have their biggest test to date as they welcome in the #5 Clemson Tigers Saturday night for the annual Red Bandana game. As to be expected, the Eagles are coming into their own home game as a +20.5 underdog and O/U at 48.5.

Now, at first glance, I thought that Vegas was being a tad bit generous in giving BC a three touchdown cushion. Against most teams in the ACC I would say take the points, but this is Clemson that we are talking about.

Dabo Sweeny continues to mold and shape is team into national championship contenders despite whomever is under center. So far, he is done an excellent job with Trevor Lawrences replacement, DJ Uiagalelei, who now in second year as the starter is starting to put up numbers akin to what we are used to seeing Clemson QBs do. He has thrown for 1,242 yards with an 11/1 TD to INT ratio putting him at a 152.6 Passer Rating. Of course, he is no T-Law, but this will certainly be the most high-powered offense BCs defense will have to date. That is a scary statemenet especially what happened down in Tallahassee a few weeks prior...

Clemson is currently averaging 41 points per contest and has had their share of tough ACC opponents to which we can get a solid sample size of the competition they have had to endure. A nail-biting finish last week against NC State along with a double overtime win on the road against Wake Forest were certainly the two games that jump off the page the most. In years past, those would have been somewhat concerning contests, but this years ACC is stacked with talent and NC State and Wake Forest have proven that they can compete with the best and are worthy of Top 25 rankings making Clemsons victories in those environments all the more noteworthy.

Getting in to the numbers, the Tigers go into their match against the Eagles averaging 437 yards of total offense split between 261 through the air and 175.8 on the ground. Will Shippley continues to be a menace on the ground as he ranks 39th in the FBS in yards at 413 on the season to go along with 7 touchdowns.

On the defensive side of the ball, the Tigers are one of the most resilient rushing defenses in FBS. To date, they have only given up 69.6 yards on average on the ground. That is a mind boggling stat. Through the air, they are a bit mor susceptible allowing 263 yards per game.

So, what does this all mean for the Eagles who are looking to snap an 11 game losing streak to the Tigers? Well, not a whole lot. BC has tried to establish some type of run game all season to no avail aside from last week against Louisville. With this Clemson defensive front, I forsee a lot of no-gain carries and quite a few pressured pockets that Jurkovec will try to throw out of.

With all this said, it is really going to come down on how our defense can perform throughout this contest and allow our offense to break off some trickey and big plays that we have seen in years past. BC has proven to have a sturdy defense this season allowing just 218 passing yards per game and 154 on the ground.

My prediction will be that, despite all this, I would take Clemson -20.5 this week along with the Over. Like I have seen time and again, it really is only a matter of time before the levee breaks with this defense. As a loose gamescript, I think that BCs defense has a few solid stops in the first two quarters of play, our offense cannot get anything going and eventually it becomes too much weight for our defense to carry. The game ultimately collapses come the second half. Expect the final score to end up somewhere around 45-17.

Prediction: Clemson -20.5 | Over 48.5 | Clemson (-1600)

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Father who blew 100K on bets reveals how TikTok saved him from gambling – The Independent

Posted: at 1:21 pm

A father who spent more than 100,000 on bets before losing everything is now helping other gambling addicts to quit through TikTok.

James Nixon, 30, who works in business development and lives in Andover, Hampshire, spent three years couch surfing after losing his home, relationship and children due to a gambling addiction which saw him lose thousands of pounds each month.

Having quit in 2018, he relapsed when the Covid pandemic saw his addiction meetings halted and it was not until July 2022 that he managed to get it under control again.

Now James, who has two children aged seven and 10 whom he does not wish to name, uses social media to help others end their gambling habits posting about his own experiences to encourage addicts to quit.

James said: My pay used to go into my bank account at around three in the morning and, by five or six, Id be asking people for money because Id spent everything.

I dont know exactly how much Ive lost throughout my addiction but it is definitely over 100,000.

Hearing that Ive been a factor in someone else stopping is amazing.

James Nixon

He recalls how he first became hooked on gambling as a teenager growing up in a seaside town surrounded by arcades before the addiction escalated into adulthood, when he used money, needed for food and bills for his family, to place football bets.

James said: I started going to the arcades when I was about 16. My friends used to hang around there and play on the games.

For them, it was a bit of fun to pass the time but for me, I got really into it and played them loads.

He added: Then, I went to the bookies with my ex-girlfriends dad and we placed a couple of bets. I had quite a big win and from there, I was hooked.

James began regularly placing bets on online sports, particularly tennis and football.

He said: At first, I was making excuses as to why I had no money and why I needed to borrow from people but over time, people started getting suspicious.

He added: I couldnt hide it any longer, when I started getting spotted at the bookies or gambling related things would pop up on my phone.

At the time, James was living with his then-partner.

He said: She knew I was gambling a lot because I would talk about how winning the latest bet would solve our money worries.

At first, I was making excuses as to why I had no money and why I needed to borrow from people but over time, people started getting suspicious.

James Nixon

He added: I would ask her for money to place bets when I ran out and gambling became the start of a lot of arguments.

I would always be selfish and use the money we needed to place bets and would inevitably lose it, then wed have to make do with what little food we had and we would be behind on bills.

Id usually be in a bad mood too because Id lost.

By this point, James had realised he had a gambling addiction but could not kick the habit.

He said: It was always a case of, the next one will be a win that kept me hooked.

I lost everything, my relationship, my kids, my home.

James relationship broke down in 2015 and he spent the next two years couch surfing.

He said: Id stay with different friends and family over the years and I dont think that helped because, if I moved around a lot, I wasnt staying with the same people for too long and it was easier to cover up just how bad the problem was.

It took another three years for me to stop gambling completely. I had to completely lose everything in my life to finally stop.

I would always be selfish and use the money we needed to place bets and would inevitably lose it.

James Nixon

In 2018, after losing some friends due to borrowing money he could not pay back, James finally stopped gambling and started to attend addiction meetings.

He said: The meetings really helped me but when the first Covid lockdown hit in March 2020, the meetings stopped.

I was finding it harder and harder to stay on course and, after a while, I relapsed.

I hope I can help other people through TikTok.

James Nixon

With his credit score on the mend after three years of being financially responsible, James was able to take out loans to gamble.

He said: It was a slippery slope and getting out of control. I was losing thousands of pounds and my debt was escalating.

It wasnt until July this year that I finally stopped. I dont think there was a particular reason, it was just that I knew it was out of control.

He added: I was heading down the same route as before and it scared me.

After quitting again, James started to upload videos about his journey to TikTok.

He said: I had already been using the app and had seen other people make similar videos.

I was trapped when I was gambling, it wasnt a choice I wanted to make.

James Nixon

He added: I hoped that by sharing my experience it would make me more accountable and less likely to fall back into old habits.

One of the videos talking about my past went viral and people started reaching out to me, asking how they can stop too, which spurred me to make more videos.

But James admits his videos have also gained negative feedback.

It took another three years for me to stop gambling completely. I had to completely lose everything in my life to finally stop.

James Nixon

He said: I do get hateful comments too. People say I was selfish for what I did and I hold my hands up and agree with them.

I think theres a judgement attached with gambling addictions because its not a physical addiction so people see it as a choice.

I was trapped when I was gambling it wasnt a choice I wanted to make but I hope I can help other people through TikTok.

James has also been told that his content has helped other gambling addicts to quit.

He said: Those kind of messages keep me going. Hearing that Ive been a factor in someone else stopping is amazing.

Ive had friends who hadnt known about my gambling addiction reach out to me and say well done on spreading awareness.

I think theres a judgement attached with gambling addictions because its not a physical addiction so people see it as a choice.

James Nixon

He added: I think the more people who speak about it, the easier it will be for people to seek help.

Im very open about my gambling addiction, even at work, because Im determined to change and not only learn from what happened but also make sure it never happens again.

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Father who blew 100K on bets reveals how TikTok saved him from gambling - The Independent

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UK Online Gambling Gets More Complicated as EU Compliance is Scrapped – Casino.Org News

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Posted on: October 4, 2022, 10:56h.

Last updated on: October 4, 2022, 11:30h.

As the UK continues to transition away from its participation in the European Union (EU), the country is going through a significant period of financial turmoil. The decision to exit the EUs General Data Protection Regulation (GDPR) program could spell more disaster, including for gaming operators.

The UKs new prime minister, Liz Truss, has decided that the country doesnt need the GDPR. Its an idea that has been circulating as long as talk of Brexit, but which is now apparently becoming a reality.

Secretary of State for Digital, Culture, Media and Sport (DCMS) Michelle Donelan confirmed Tuesday that the UK will replace the EUs data privacy act with a new set of rules. This can only mean that gaming operators will have to contend with two systems, one for the EU and another for the UK.

The decision to dump the GDPR isnt a surprise the UK announced four months ago that something was in the works. The country will introduce its own data protection and digital information bill at some point, although its taking longer than the government initially hoped.

Although the UK has discussed creating its own rules for a couple of years, the overall concept remained aligned with the EUs guidelines. The EU signed off on the recommended proposals last year, though it said that it would be ready to pull back if the UK implemented too many changes.

I am announcing that we will be replacing GDPR with our own business and consumer-friendly, British data protection system. Our plan will protect consumer privacy and keep their data safe, whilst retaining our data adequacy so businesses can trade freely, Donelan said.

Donelan has tried to calm any concerns, explaining that the country can protect consumer data without far-reaching regulations. She stated that this is already done in countries like Japan and New Zealand, and that the UK will learn from those policies.

She also asserted that the move would make it easier for businesses to operate. However, this sentiment isnt shared by those businesses. UK companies that serve the EU will have to comply with two sets of rules.

The same applies to companies outside the UK. They have to implement solutions that can ensure adherence to both the GDPR and the UKs own solution. For many, this means double the expense related to consumer protection.

When the EU introduced the GDPR in 2016 it was hailed as one of the biggest achievements in modern history. Europe said at the time that the new rules would save billions of dollars in expenses. Introduction of the policy would also lead to efficient operations across the continent.

The data paints a different picture. Economists with Oxford University dove into the outcome of GDPR and what it meant for commercial activity earlier this year. What they found was that EU businesses lost on average 8.1% of their profits.

Small- and medium-sized enterprises lost 8.5%, while large companies lost around 7.9%. Even larger tech companies, like Google and Apple, saw no significant impacts from the implementation of the GDPR.

This doesnt instill confidence in the UKs latest effort. With inflation out of control and no fix in sight, the economy could potentially take another hit.

The good news is that, at least for now, the countrys version of the GDPR isnt moving forward. Just like new gambling regulations, theres an outside chance that nothing will change. The UK will hold new general elections in 18 months, which could usher in a new batch of political leaders.

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My trip to Atlantic City was worth it even with no gambling – New Jersey 101.5 FM

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My wife and I spent the weekend in Atlantic City to celebrate our 30th wedding anniversary.

Neither of us is a gambler, so we went for the hotel experience and the boardwalk. The nasty weather put the kibosh on the boardwalk (thanks Ian), so went we mainly spent the trip visiting hotels.

The one we stayed in, the Ocean Casino Resort, was by far the nicest.

For one thing, at the Ocean, they believe in natural light. When we walked into the lobby, I was struck by how light and airy the tall ceiling and giant windows made the place feel. I was used to rather dark casinos, but the Ocean is different. When visiting other casinos during our trip, they just seemed older and darker.

Bill Doyle photo

The Ocean is easy to find; its the tallest building in Atlantic City (Im told its the fourth tallest building in the state). Our room was on the 40th floor facing the ocean, so we had a good view of the churning waves caused by the remnants of Hurricane Ian. The Ferris wheel on the Steel Pier is really cool looking at night when it is all lit up.

The Ocean AC via Facebook

The casino floor bursts with color.

The Ocean lives up to its name as a resort given all the amenities it offers; there is a spa (complete with massages, sauna, facials, peels, and more). There is also a fully equipped fitness center (yes, I used it), and an indoor/outdoor pool (which I did not use).

The Ocean AC via Facebook

When its lit up, its visible for miles.

The restaurant selection is pretty impressive, too. Our favorite was Harpers, which only serves breakfast and lunch. Im not lying when I say they had the biggest breakfast portions Ive ever had.

I ordered assuming the portions would be small and when they brought the food to the table I realized that I had ordered too much. But I went ahead and ate it all.

My wife, who isnt as much of a pig as I am, got a doggy bag for her cinnamon roll that was about the size of her head (I exaggerate, but not by much).

The Ocean AC via Facebook

All in all, even with the bad weather, we had a great trip to AC.

Opinions expressed in the post above are those of New Jersey 101.5 talk show host Bill Doyle only.

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My trip to Atlantic City was worth it even with no gambling - New Jersey 101.5 FM

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Blueprint for an AI Bill of Rights – The White House

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Among the great challenges posed to democracy today is the use of technology, data, and automated systems in ways that threaten the rights of the American public. Too often, these tools are used to limit our opportunities and prevent our access to critical resources or services. These problems are well documented. In America and around the world, systems supposed to help with patient care have proven unsafe, ineffective, or biased. Algorithms used in hiring and credit decisions have been found to reflect and reproduce existing unwanted inequities or embed new harmful bias and discrimination. Unchecked social media data collection has been used to threaten peoples opportunities, undermine their privacy, or pervasively track their activityoften without their knowledge or consent.

These outcomes are deeply harmfulbut they are not inevitable. Automated systems have brought about extraordinary benefits, from technology that helps farmers grow food more efficiently and computers that predict storm paths, to algorithms that can identify diseases in patients. These tools now drive important decisions across sectors, while data is helping to revolutionize global industries. Fueled by the power of American innovation, these tools hold the potential to redefine every part of our society and make life better for everyone.

This important progress must not come at the price of civil rights or democratic values, foundational American principles that President Biden has affirmed as a cornerstone of his Administration. On his first day in office, the President ordered the full Federal government to work to root out inequity, embed fairness in decision-making processes, and affirmatively advance civil rights, equal opportunity, and racial justice in America.[i] The President has spoken forcefully about the urgent challenges posed to democracy today and has regularly called on people of conscience to act to preserve civil rightsincluding the right to privacy, which he has called the basis for so many more rights that we have come to take for granted that are ingrained in the fabric of this country.[ii]

To advance President Bidens vision, the White House Office of Science and Technology Policy has identified five principles that should guide the design, use, and deployment of automated systems to protect the American public in the age of artificial intelligence. The Blueprint for an AI Bill of Rights is a guide for a society that protects all people from these threatsand uses technologies in ways that reinforce our highest values. Responding to the experiences of the American public, and informed by insights from researchers, technologists, advocates, journalists, and policymakers, this framework is accompanied by From Principles to Practicea handbook for anyone seeking to incorporate these protections into policy and practice, including detailed steps toward actualizing these principles in the technological design process. These principles help provide guidance whenever automated systems can meaningfully impact the publics rights, opportunities, or access to critical needs.

Safe and Effective Systems

You should be protected from unsafe or ineffective systems. Automated systems should be developed with consultation from diverse communities, stakeholders, and domain experts to identify concerns, risks, and potential impacts of the system. Systems should undergo pre-deployment testing, risk identification and mitigation, and ongoing monitoring that demonstrate they are safe and effective based on their intended use, mitigation of unsafe outcomes including those beyond the intended use, and adherence to domain-specific standards. Outcomes of these protective measures should include the possibility of not deploying the system or removing a system from use. Automated systems should not be designed with an intent or reasonably foreseeable possibility of endangering your safety or the safety of your community. They should be designed to proactively protect you from harms stemming from unintended, yet foreseeable, uses or impacts of automated systems. You should be protected from inappropriate or irrelevant data use in the design, development, and deployment of automated systems, and from the compounded harm of its reuse. Independent evaluation and reporting that confirms that the system is safe and effective, including reporting of steps taken to mitigate potential harms, should be performed and the results made public whenever possible.

From Principles to Practice: Safe and Effective Systems

Algorithmic Discrimination Protections

You should not face discrimination by algorithms and systems should be used and designed in an equitable way. Algorithmic discrimination occurs when automated systems contribute to unjustified different treatment or impacts disfavoring people based on their race, color, ethnicity, sex (including pregnancy, childbirth, and related medical conditions, gender identity, intersex status, and sexual orientation), religion, age, national origin, disability, veteran status, genetic information, or any other classification protected by law. Depending on the specific circumstances, such algorithmic discrimination may violate legal protections. Designers, developers, and deployers of automated systems should take proactive and continuous measures to protect individuals and communities from algorithmic discrimination and to use and design systems in an equitable way. This protection should include proactive equity assessments as part of the system design, use of representative data and protection against proxies for demographic features, ensuring accessibility for people with disabilities in design and development, pre-deployment and ongoing disparity testing and mitigation, and clear organizational oversight. Independent evaluation and plain language reporting in the form of an algorithmic impact assessment, including disparity testing results and mitigation information, should be performed and made public whenever possible to confirm these protections.

From Principles to Practice: Algorithmic Discrimination Protections

Data Privacy

You should be protected from abusive data practices via built-in protections and you should have agency over how data about you is used. You should be protected from violations of privacy through design choices that ensure such protections are included by default, including ensuring that data collection conforms to reasonable expectations and that only data strictly necessary for the specific context is collected. Designers, developers, and deployers of automated systems should seek your permission and respect your decisions regarding collection, use, access, transfer, and deletion of your data in appropriate ways and to the greatest extent possible; where not possible, alternative privacy by design safeguards should be used. Systems should not employ user experience and design decisions that obfuscate user choice or burden users with defaults that are privacy invasive. Consent should only be used to justify collection of data in cases where it can be appropriately and meaningfully given. Any consent requests should be brief, be understandable in plain language, and give you agency over data collection and the specific context of use; current hard-to-understand notice-and-choice practices for broad uses of data should be changed. Enhanced protections and restrictions for data and inferences related to sensitive domains, including health, work, education, criminal justice, and finance, and for data pertaining to youth should put you first. In sensitive domains, your data and related inferences should only be used for necessary functions, and you should be protected by ethical review and use prohibitions. You and your communities should be free from unchecked surveillance; surveillance technologies should be subject to heightened oversight that includes at least pre-deployment assessment of their potential harms and scope limits to protect privacy and civil liberties. Continuous surveillance and monitoring should not be used in education, work, housing, or in other contexts where the use of such surveillance technologies is likely to limit rights, opportunities, or access. Whenever possible, you should have access to reporting that confirms your data decisions have been respected and provides an assessment of the potential impact of surveillance technologies on your rights, opportunities, or access.

From Principles to Practice: Data Privacy

Notice and Explanation

You should know that an automated system is being used and understand how and why it contributes to outcomes that impact you. Designers, developers, and deployers of automated systems should provide generally accessible plain language documentation including clear descriptions of the overall system functioning and the role automation plays, notice that such systems are in use, the individual or organization responsible for the system, and explanations of outcomes that are clear, timely, and accessible. Such notice should be kept up-to-date and people impacted by the system should be notified of significant use case or key functionality changes. You should know how and why an outcome impacting you was determined by an automated system, including when the automated system is not the sole input determining the outcome. Automated systems should provide explanations that are technically valid, meaningful and useful to you and to any operators or others who need to understand the system, and calibrated to the level of risk based on the context. Reporting that includes summary information about these automated systems in plain language and assessments of the clarity and quality of the notice and explanations should be made public whenever possible.

From Principles to Practice: Notice and Explanation

Human Alternatives, Consideration, and Fallback

You should be able to opt out, where appropriate, and have access to a person who can quickly consider and remedy problems you encounter. You should be able to opt out from automated systems in favor of a human alternative, where appropriate. Appropriateness should be determined based on reasonable expectations in a given context and with a focus on ensuring broad accessibility and protecting the public from especially harmful impacts. In some cases, a human or other alternative may be required by law. You should have access to timely human consideration and remedy by a fallback and escalation process if an automated system fails, it produces an error, or you would like to appeal or contest its impacts on you. Human consideration and fallback should be accessible, equitable, effective, maintained, accompanied by appropriate operator training, and should not impose an unreasonable burden on the public. Automated systems with an intended use within sensitive domains, including, but not limited to, criminal justice, employment, education, and health, should additionally be tailored to the purpose, provide meaningful access for oversight, include training for any people interacting with the system, and incorporate human consideration for adverse or high-risk decisions. Reporting that includes a description of these human governance processes and assessment of their timeliness, accessibility, outcomes, and effectiveness should be made public whenever possible.

From Principles to Practice: Human Alternatives, Consideration, and Fallback

While many of the concerns addressed in this framework derive from the use of AI, the technical capabilities and specific definitions of such systems change with the speed of innovation, and the potential harms of their use occur even with less technologically sophisticated tools.

Thus, this framework uses a two-part test to determine what systems are in scope. This framework applies to (1) automated systems that (2) have the potential to meaningfully impact the American publics rights, opportunities, or access to critical resources or services. These Rights, opportunities, and access to critical resources of services should be enjoyed equally and be fully protected, regardless of the changing role that automated systems may play in our lives.

This framework describes protections that should be applied with respect to all automated systems that have the potential to meaningfully impact individuals or communities exercise of:

Rights, Opportunities, or Access

Civil rights, civil liberties, and privacy, including freedom of speech, voting, and protections from discrimination, excessive punishment, unlawful surveillance, and violations of privacy and other freedoms in both public and private sector contexts;

Equal opportunities, including equitable access to education, housing, credit, employment, and other programs; or,

Access to critical resources or services, such as healthcare, financial services, safety, social services, non-deceptive information about goods and services, and government benefits.

A list of examples of automated systems for which these principles should be considered is provided in the Appendix. The Technical Companion, which follows, offers supportive guidance for any person or entity that creates, deploys, or oversees automated systems.

Considered together, the five principles and associated practices of the Blueprint for an AI Bill of Rights form an overlapping set of backstops against potential harms. This purposefully overlapping framework, when taken as a whole, forms a blueprint to help protect the public from harm. The measures taken to realize the vision set forward in this framework should be proportionate with the extent and nature of the harm, or risk of harm, to peoples rights, opportunities, and access.

[i] The Executive Order On Advancing Racial Equity and Support for Underserved Communities Through the FederalGovernment. https://www.whitehouse.gov/briefing-room/presidential-actions/2021/01/20/executive-order-advancing-racial-equity-and-support-for-underserved-communities-through-the-federal-government/

[ii] The White House. Remarks by President Biden on the Supreme Court Decision to Overturn Roe v. Wade. Jun. 24, 2022. https://www.whitehouse.gov/briefing-room/speeches-remarks/2022/06/24/remarks-by-president-biden-on-the-supreme-court-decision-to-overturn-roe-v-wade/

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Get ready for the next generation of AI – MIT Technology Review

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Researchers from Google also submitted a paper to the conference about their new model calledDreamFusion, which generates 3D images based on text prompts. The 3D models can be viewed from any angle, the lighting can be changed, and the model can be plonked into any 3D environment.

Dont expect that youll get to play with these models anytime soon.Meta isn't releasing Make-A-Video to the public yet. Thats a good thing. Metas model is trained using the same open-source image-data set that was behind Stable Diffusion. The company says it filtered out toxic language and NSFW images, but thats no guarantee that they will have caught all the nuances of human unpleasantness when data sets consist of millions and millions of samples. And the company doesnt exactly have a stellar track record when it comes to curbing the harm caused by the systems it builds, to put it lightly.

The creators of Pheraki write in theirpaperthat while the videos their model produces are not yet indistinguishable in quality from real ones, it is within the realm of possibility, even today. The models creators say that before releasing their model, they want to get a better understanding of data, prompts, and filtering outputs and measure biases in order to mitigate harms.

Its only going to become harder and harder to know whats real online, and video AI opens up a slew of unique dangers that audio and images dont, such as the prospect of turbo-charged deepfakes. Platforms like TikTok and Instagram are alreadywarping our sense of realitythrough augmented facial filters. AI-generated video could be a powerful tool for misinformation, because people have a greater tendency to believe and share fake videos than fake audio and text versions of the same content,accordingto researchers at Penn State University.

In conclusion, we havent come even close to figuring outwhat to do about thetoxic elements of language models. Weve only just started examining the harms around text-to-image AI systems. Video? Good luck with that.

The EU wants to put companies on the hook for harmful AI

The EU is creating new rules to make it easier to sue AI companies for harm.A new bill published last week, which is likely to become law in a couple of years, is part of a push from Europe to force AI developers not to release dangerous systems.

The bill, called the AI Liability Directive, will add teeth to the EUsAI Act, which is set to become law around a similar time. The AI Act would require extra checks for high risk uses of AI that have the most potential to harm people. This could include AI systems used for policing, recruitment, or health care.

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To Improve AI Outcomes, Think About the Entire System – HBR.org Daily

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CURT NICKISCH: Welcome to the HBR IdeaCast from Harvard Business Review. Im Curt Nickisch.

A shiny new piece of technology is not good enough on its own. It needs to be implemented at the right time, used in the right context, and accepted in the right culture, applied in the right way. In short, it needs to be part of the right system. And thats true for artificial intelligence too. AI can help individuals and teams make better predictions, combine that with judgment and you get better decisions. But those decisions have ripple effects on other parts of the system, ripple effects that can undermine the very prediction that was made.

Our guest today says, If organizations want to take artificial intelligence to the next level, they need to get better at coordinating optimal decisions over a wider network. Joshua Gans is a strategy professor at the University of Torontos Rotman School of Management. He co-wrote the HBR article, From Prediction to Transformation, as well as the new book, Power and Prediction: The Disruptive Economics of Artificial Intelligence.

Hi, Joshua.

JOSHUA GANS: Hi.

CURT NICKISCH: One big argument is that artificial intelligence has to do more for companies than just give data and insights. Is that like a big misconception that people have about AI? Theyre going to get insights out of their data and thats just not enough?

JOSHUA GANS: Yeah, so I think what happened some years ago, relatively recently, I guess, is that, of course, we started the hype about artificial intelligence. Businesses who are attuned to technological developments, started asking whether this was going to be something that should concern them or could take advantage of? And the one thing that artificial intelligence, in its recent incarnation, required, was data, artificial intelligence, machine learning, and deep learning. The more recent stuff, not the stuff that you might see in movies, is really an advance in the statistics of prediction.

It allows you to get much more accurate predictions for dramatically lower cost. But in order to generate those predictions, you do need to have data of differing kinds. And I think one of the things that the businesses asked themselves, Well, we have a lot of data. Weve been collecting data on so and so for years, maybe actually were well positioned to have a critical input into this new technology. That led to more investment to clean up that data and make use of it. But I think there were some challenges.

CURT NICKISCH: An example of this is, I dont know, a retailer who is trying to manage their inventory better so that they dont have as much in stock, but have just enough that when somebody orders it, they have it close by or in the right location.

JOSHUA GANS: Yes. So prediction of demand is a common one, and it was a one that we wouldve thought wouldve been very, very ubiquitous. What we found that even for things like inventory, when you try to predict demand better, you have to say, Well, what am I going to do with that prediction? What Im going to do with that prediction is, if I anticipate there are going to be a surge in demand for one of my products, what I need to do, is make sure Ive got that product on hand. Well, thats easier said than done. In this world of supply constraints, there may not be simple ways of doing that. We have very tight supply chains.

And so what might happen is, you might want to adopt AI for this thing, prediction, where theres some clear uncertainty, but instead you realize that you cant fully take advantage of it, because that requires coordinating everything all the way down the line. Something that we sometimes refer to as the AI bullwhip effect basically employing AI somewhere, has reverberations down the line. And if you cant actually get the rest of the system to come along with you, you might not be getting much value out of AI in the first place.

CURT NICKISCH: Have you seen a lot of places disappointed in what theyve implemented?

JOSHUA GANS: I think relative to our expectations in 2018, the adoption of artificial intelligence beyond the biggest tech firms, has been pretty slow. There was a lot of optimism that it could be used and could be used to make certain tasks more efficient, and I think it has to some degree. But in terms of its true transformational impact, well, it turns out that just adding a dollop of AI isnt going to do it for you. AI is something that gets leveraged within a context of a system. Yes, in some systems you can just improve your prediction and that system operates better.

In other systems, things are sort of divided, a bit modular, with one another. So you can put in some AI in one part of the organization, and that org part does better and the rest of it goes merrily along. But we suspect that in fact, the biggest transformations from AI are going to require a system-wide adjustment to exploit it. And youre not going to exploit that just for a trial. Youre going to exploit that when you really think AI is going to give you that leverage, because theres a lot of work involved obviously.

CURT NICKISCH: In your article you wrote about sailing teams in the Americas Cup, what they typically need to do to win and you tell a story of how one team used AI to really excel.

JOSHUA GANS: So the Americas Cup is deep in my bones because Im an Australian and I grew up in the 1980s, and it was a significant affair. And what I always reflect about that, when Australia too, managed to win the Americas Cup, first non-American team to do so in over a 100 years. It was because of a more radical boat design, the so-called winged keel. And there was a lot of discussion of that, which was a very interesting way for Australians to win a sporting event, which is technological innovation as opposed to better training and other things that we were used to.

So that heralded an era where the Americas ocean racing like this, started to have greater technological inputs. So when it came to the application of artificial intelligence, artificial intelligence has the ability to look at conditions, look at behaviors, and predict better performance, and then to say, Well, if we change the design this way, or that way, or something completely different, what might be the likely change in performance? Because it can basically handle all those weird edge cases that people dont normally think of.

And moreover, it can do it in the context of providing simulations. Now initially, the production process for coming up with new designs, was to put in a new design and then put it into a simulation where you had people operate the sailing boat as they would. One problem with that is, of course, every iteration takes time. Every iteration takes somebody going out and running several hours or maybe even more, of simulation.

CURT NICKISCH: Cant do that at night, yeah.

JOSHUA GANS: Yeah, you cant do it. So what was interesting there, one of the things that had happened about the same time, was that wed had these advances in the playing of games like Go. Artificial intelligence initially became the world champion at Go, by looking at all the games that everybody had ever played, and using that to predict moves and predict winning strategies, and come up with better winning strategies. Soon after that, they wondered, Well, what if we forget the people together and just have these AIs play even more games against each other, and not limited to the total corpus of recorded games.

So Team New Zealand saw that and said, Well, maybe we can just program in responses of people, automate them, not try to get too fancy about it, not to think about what theyre seeing, et cetera, and run a heap more simulations. As a result, that iterate even faster. That may lead to a system where you think, Oh, well, then youre not going to need a person to run that sailing boat at all. But actually, this is typical. The one place where systems seem to be starting to really work in AI, is in innovation itself.

CURT NICKISCH: Well, sorting through complicated problems, thinking about how one decision will affect another, that sounds a lot like what people are supposed to do at work, but a lot of organizations have this capability for AI in one place or with one data science team. Where does this need to change?

JOSHUA GANS: Think about what happens when you are dealing with a lot of uncertainty and you cant predict it. One of our favorite examples is just the decision whether you carry an umbrella or not. If you have no forecast of the weather, well, it depends on your own preferences. How much do you want to get wet versus how much youd mind carrying an umbrella? Its essentially the choice. And so youll have a rule for it. Even if I give you a prediction of the rain, that might only slightly modify your rules. Lets say, if theres zero chance of rain, sure, I wouldve taken an umbrella but I personally even think 20% would be worrisome, so I would. So people have some specific rules. So you think about that now in the context of business, when were not dealing just with whether it rains or not, but a whole heap of uncertainty.

Well, if youve been unable to predict that uncertainty, youve been unable to adjust your organization to it, at least before the fact. And so a good way to deal with that, is to do what we do, is develop rules. So we take what might have been a decision, something where we, Oh, if we think this is going to happen, do X. If we think something else is going to happen, do Y. And we say, Well, we dont know whats going to happen, so we just choose X or Y. And we put that into our organization. Sometimes we come up with whole standard operating procedures where people have thought very deeply about what the best guide is for people when you just cant react to everything thats going on.

And so those are the successful organizations. Now, I am an AI salesman coming in and saying, Oh, you need to adopt AI. Well, what does that mean? What does that mean, is that means were going to give you some predictions of some of these things youre missing and now you can make a decision, you can react to it. Thats got to be a better thing to do. And youre saying to yourself, I dont have any decisions. Weve got all these rules. And a few years pass and some employee turnover, you might dont even know. You might know the rules work, but you might not realize that the rules were a reaction to uncertainty and were made so you didnt have to think about the uncertainty.

So its really hard for you to sell something to an organization when their organizations constructed itself, not to realize that they need it or could use it, or even worse, realize that and realize its going to have to change everything, which is a little scary. So thats where we see disruption coming in, artificial intelligence requiring the organizations to break out of things that they were doing. Now, some large organizations can realize that or maybe theyve got more flexibility and they can integrate it, but typically, that is a recipe for new entrants who are not starting off, Oh, we are doing these rules starting off with some other basis, and were going to use AI to come in and do things better.

CURT NICKISCH: When you say new entrants, are you talking about competitors?

JOSHUA GANS: Yeah, competitors, startups, things like that. Whereas, if you get a startup firm, well, they dont have any legacy. They dont have to change how theyre doing things. Theyre not doing anything. So theyre building right from the start, from a green field essentially. And for these sorts of innovations that require a brand new system, its easier to start from scratch in some regards. So thats where that competitive tension comes in.

CURT NICKISCH: Yeah. So youre saying that it needs to be done differently going forward, but a lot of organizations just arent prepared to do that?

JOSHUA GANS: Yeah, I mean, think there is an appetite. I mean, theres enough business school and HBR reading to know that these things are an issue. So CEOs will look at it and say, This has the potential to disrupt. Maybe I should do something.

CURT NICKISCH: And Im just curious, what should that CEO do? If theyre at an organization and youve got some AI technology, but its in a team, in one place, or in a silo, and theyre improving decisions iteratively, but not really realizing the full system power of implementing AI, what should that CEO do?

JOSHUA GANS: This is where they earn their money, from these. This is a nasty, nasty problem. All the things are pushing towards doing nothing or to waiting and seeing, but changing your systems going to take time. Really, what you want to have in an organization is, you want to make it easier on yourself by having organizational memory of why you are where you are. So remember I said before, you have rules and then you forget why you had the rule.

Thats going to be a problem. So what you want to do is, you want to design an organization such that that memory is being filtered through quite regularly. And moreover, people have some flexibility, so that when you come to do these organizational redesigns, its not as painful for everybody. But thats a tension, because you are betting on the long-term or something potential, and youre going to sacrifice something now, by preparing for it. Thats essentially the real dilemma of disruption.

CURT NICKISCH: Youve given executives and leaders an out here, to know that this is hard, but what are some of the systems that companies should think about changing, to prepare for this?

JOSHUA GANS: So one of the things we try to encourage organizations when we sit down to talk about that, is we say, Can you go through an exercise where you can identify the big uncertainty you are facing in an organization? And what that is? So we might sit down with a hospital and ask them, and not even hospital system, just a hospital, What are the big uncertainties? And theres all sorts of things. What are the new techniques were going to put in? What are the costs of getting doctors, nurses, and so on? Oh, yeah, how were going to manage capacity? How are we going to make sure weve got enough beds for the demands in the local community? Im like, Well, thats an interesting one. Okay, why are you having trouble with that?

Well, one reason is things like COVID. Okay, of course. But the other is, the population changes and we build a hospital, but we cant change it very often, the population changes, and saying, Well, thats interesting. Youre talking about it in terms of people and youre uncertain about the number of people. What about the length of their stay? And they come back and say, Oh, no, no, thats standard. If you have this procedure, youll be there for that long, et cetera, et cetera. Im like, Ah, theres a word Im going to clue on, standard. Why is that standard? Well, if somebody gets an appendicitis, you need to keep them there a few days to make sure that they dont get an infection and secondary things, and other things like that. And so its a standard thing.

Or some other procedures, which it might be five days, or a week, or what have you. Because weve got to keep them under observation. Complications occur, and Im like, Oh, so theyre sitting in the bed, waiting for that information and you are waiting for that information. What if you actually, at the time of the operation, had enough information that you can make a really great prediction about how out of the woods somebody is or not? Ah, that changes everything. And now we go through the full experiment, Well, lets just go to the extreme and imagine you could perfectly predict that. And all of a sudden itd be, Wow, wed have a lot more hospital space all of a sudden. In fact, most of our people are sitting in bed waiting for stuff and if we had this knowledge.

And I said, Well, if you had some of this knowledge before they came into the hospital? What if you were collecting data on patients in the population before, so that when they get to the hospital, youre not reacting and trying to work out what they have, but you have a good idea about whats going on. Im like, Again. And that gets you down to this one variable, which is major, which is capacity in the hospital, and its telling you that all of a sudden your issue is not that youre going to be running up against capacity constraints, is that if you got this AI magically tomorrow, youd have a lot of spare capacity.

CURT NICKISCH: Right. But it sounds complicated.

JOSHUA GANS: It is complicated and Ive glossed over a lot to get there, but thats the sort of thing a CEOs going to have to go through. Thinking through those sorts of scenarios and really trying to understand one or two things that if they could develop AI for, it would change everything. Because thats the real worry. Developing AI for some of the other things on the fringes, its not going to be an existential threat or even a major opportunity, but developing AI thats going to turn a business around, change how you think about major decisions like capital, or expansions, and stuff like that, thats a whole other matter.

CURT NICKISCH: System change takes time. Is it a danger if the ability to change the system, takes longer than it does for the technology to improve?

JOSHUA GANS: Is it a danger? I dont know. I think the technology will reach technical improvements at a much faster rate, than the systems will change for it. This is not unprecedented. In electricity, Thomas Edison lit up the streets of a suburb of New York, and it was 40 years before more than half the country started to have electricity going to their factories and to their houses. This stuff takes time, let alone with electricity, it did lead to a transformation of manufacturing and other businesses, and that didnt happen for decades.

CURT NICKISCH: Whats your recommendation for a manager or somebody in a company, who feels like they need to be doing more but the organization isnt, and they want to spur some change?

JOSHUA GANS: One of the things that weve found with thinking about changes in systems, is that they very rarely occur without changes in power. There are winners and there are losers. We saw this for the taxi cab industry when ride-sharing came into play and ride-sharing came into play because people had mobile devices, and so any driver would have the locational and navigational ability of the most experienced taxi driver. And the power change that occurred there, was power to individual drivers and power away from taxi drivers who previously had something that was more unique. This sort of thing is likely to occur within organizations as well.

Now sometimes we talk a lot about automation just replacing jobs and things like that, all these changes tend to be a bit more subtle, but one of the challenges of managing that change, is understanding where power is changing and where youre going to get resistance from. Broadly speaking, that just means being a good manager. That must mean understanding peoples perspectives and points of view, with transformational things that is just as important as day-to-day things, and you just have to have a plan for it. Some of that plan may be that you decide to ignore or cast off some of the more resisting parts, but obviously the potential opportunity is to see if you can co-op them.

CURT NICKISCH: Joshua, thanks so much for coming on the show to talk about this.

JOSHUA GANS: Thank you.

CURT NICKISCH:Thats Joshua Gans. He is a professor at the University of Torontos Rotman School of Management. The chief economist at the Creative Destruction Lab, and a co-author of the HBR article, From Prediction to Transformation. He also co-wrote the new book, Power and Prediction.

If you got something from todays episode, we have more podcasts to help you manage your team, manage organizations, and manage your career. Find them at hbr.org/podcast or search HBR in Apple Podcasts, Spotify, or wherever you listen.

This episode was produced by Mary Dooe. We get technical help from Rob Eckhardt. Our audio product manager is Ian Fox and Hannah Bates is our audio production assistant. Thanks for listening to the HBR IdeaCast. Im Curt Nickisch.

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