Category Archives: Decision Making

Cognitive Bias and the Gun Debate

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I teach a course at my Canadian university on the Psychology of Thinking and in this course, we discuss topics like concept formation, decision making, and reasoning. Many of these topics lend themselves naturally to the discussion of current topics and in one class last year, after a recent mass shooting in the US, I posed the following question:

“How many of you think that the US is a dangerous place to visit?”

About 80% of the students raised their hands. This is surprising to me because although I live and work in Canada and I’m a Canadian citizen, I grew up in the US; my family still lives there and I still think it’s a reasonably safe place to visit. Most students justified their answer by referring to school shootings, gun violence, and problems with American police. Importantly, none of these students had ever actually encountered violence in the US. They were thinking about it because it has been in the news. That were making a judgment on the basis of the available evidence about the likelihood of violence.

Cognitive Bias

The example above is an example of a cognitive bias known as the Availability Heuristic. The idea, originally proposed in the early 1970s by Daniel Kahneman and Amos Tversky (Kahneman & Tversky, 1979; Tversky & Kahneman, 1974) is that people generally make judgments and decisions on the basis of the most relevant memories that they retrieve and that are available at the time that the assessment or judgement is made. In other words, when you make a judgment about a likelihood of occurrence, you search your memory and make your decision on the basis of what you remember. Most of the time, this heuristic produces useful and correct evidence. But in other cases, the available evidence may not correspond exactly to evidence in the world. For example, we typically overestimate the likelihood of shark attacks, airline accident, lottery winning, and gun violence.

Another cognitive bias (also from Kahneman and Tversky) is known as the Representativeness Heuristic. This is the general tendency to treat individuals as representative of their entire category. For example, suppose I formed concept of American gun owners as being violent (based on what I’ve read or seen in the news), I might infer that each individual American is a violent gun owner. I’d be making a generalization or a stereotype and this can lead to bias in how a treat people. As with availability, the representativeness heuristic arrises out of the natural tendency of humans to generalize information. Most of the time, this heuristic produces useful and correct evidence. But in other cases, the representative evidence may not correspond exactly to individual evidences in the world.

The Gun Debate in the US

I’ve been thinking about this a great deal as the US engages in their ongoing debate about gun violence and gun control. It’s been reported widely that the US has the highest rate of private gun ownership in the world, and also has an extraordinary rate of gun violence relative to other counties. These are facts. Of course, we all know that “correlation does not equal causation” but many strong correlations often do derive from a causal link. The most reasonable thing to do would be to begin to implement legislation that restricts access to firearms but this never happens and people are very passionate about the need to restrict guns.

So why to do we continue to argue about this? One problem that I rarely see being discussed is that many of us have limited experience with guns and/or violence and have to rely on what we know from memory and from external source and we’re susceptible to cognitive biases.

Let’s look at things from the perspective of an average American gun owner. This might be you, people you know, family, etc. Most of these gun owners are very responsible, knowledgeable, and careful. They own firearms for sport and also for personal protection and in some cases, even run successful training courses for people to learn about gun safety. From the perspective of a responsible and passionate gun owner, it seems to be quite true that the problem is not guns per se but the bad people who use them to kill others. After all, if you are safe with your guns and all your friends and family are safe, law abiding gun owners too, then those examples will be the most available evidence for you to use in a decision. And so you base your judgements about gun violence on the this available evidence and decide that gun owners are safe. As a consequence, gun violence is not a problem of guns and their owners, but must be a problem of criminals with bad intentions. Forming this generalization is an example of the availability heuristic. It my not be entirely wrong,  but it is a result of a cognitive bias.

But many people (and me also) are not gun owners. I do not own a gun but I feel safe at home. As violent crime rates decrease, the likelihood being a victim of a personal crime that a gun could prohibit is very small, Most people will never find themselves in this situation. In addition, my personal freedoms are not infringed by gun regulation and I too recognize that illegal guns are a problem. If I generalize from my experience, I may have difficulty understanding why people would need a gun in the first place whether for personal protection or for a vaguely defined “protection from tyranny”. From my perspective it’s far more sensible to focus on reducing the number of guns. After all, I don’t have one, I don’t believe I need one, so I generalize to assume that anyone who owns firearms might be suspect or irrationally fearful. Forming this generalization is also an example of the availability heuristic. It my not be entirely wrong,  but it is a result of a cognitive bias.

In each case, we are relying on cognitive biases to infer things about others and about guns. These things and inferences may be stifling the debate

How do we overcome this?

It’s not easy to overcome a bias, because these cognitive heuristics are deeply engrained and indeed arise as a necessary function of how the mind operates. They are adaptive and useful. But occasionally we need to override a bias.

Here are some proposals, but each involves taking the perspective of someone on the other side of this debate.

  1. Those of us on the left of the debate (liberals, proponents of gun regulations) should try to recognize that nearly all gun enthusiasts are safe, law abiding people who are responsible with their guns. Seen through their eyes, the problem lies with irresponsible gun owners. What’s more, the desire to place restrictions on their legally owned guns activates another cognitive bias known as the endowment effect in which people place high value on something that they already possess, the prospect of losing this is seen as aversive because it increases the feeling of uncertainty for the future.
  2. Those on the right (gun owners and enthusiasts) should consider the debate from the perspective of non gun owners and consider that proposals to regulate firearms are not attempts to seize or ban guns but rather attempts to address one aspect of the problem: the sheer number of guns in the US, any of which could potentially be used for illegal purposes. We’re not trying to ban guns, but rather to regulate them and encourage greater responsibility in their use.

I think these things are important to deal with. The US really does have a problem with gun violence. It’s disproportionally high. Solutions to this problem must recognize the reality of the large number of guns, the perspectives of non gun owners, and the perspectives of gun owners. We’re only going to do this by first recognizing these cognitive biases and them attempting to overcome them in ways that search for common ground. By recognizing this, and maybe stepping back just a bit, we can begin to have a more productive conversation.

As always: comments are welcome.

The Unintended Cruelty of America’s Immigration Policies

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It is well documented that the Trump administration is pursing a senselessly cruel policy of prosecuting migrants at the border, detaining families, and incarcerating them in large, improvised detention centres. This includes taking children away from their parents and siblings and housing them separately for an extended period.

Pointlessly Cruel

Jeff Sessions has pointed out that this policy is “simply enforcing the law” and that it’s a deterrent. He lays any negative conseqences on the migrant families themselves, asking why they would risk bringing their children on this long and dangerous trek. Other members of the administration have pointed out that families who claim asylum at ports of entry are not being detained or split apart. This too is disingenuous, as the Trump administration has narrowed the reasons for asylum, and as the border has become increasingly militarized, migrants and asylum-seekers are being forced away from busy ports of entry and often into dangerous crossings.

 How did we get to this point? How did a nation which once prided itself on welcoming immigrants become a nation increasingly looking to punish individuals even as they seek asylum? Although some aspects of this cruel policy have long been present in America’s history, I think that particular fixation on migration from Mexico stems from an unintended starting point.

Unintended Consequences

A recent podcast by Malcolm Gladwell explored the causes and effects of the militarized US-Mexico border. I found this podcast fascinating and I recommend listening to it. To summarize, for most of the 20th century, into the 1960s and 1970s, migration between the United States and Mexico was primarily cyclical. Migrants from rural areas near the border in Mexico would move to the United States for work, stay for a few months, and move back to Mexico with their families. This was an economic relationship and it worked because the cost of crossing the border was essentially zero. If you are apprehended, you’d be returned but otherwise it allowed for the flow of migrants into the United States and out of the United States.

In the early 1970s, however, the US-Mexico border began to be militarized. It happened almost by accident. An extremely skilled and dedicated retired Marine General took over immigration and naturalization services and began to tighten up the way in which border patrols operated. There was never any intent to cause suffering.  On the contrary, the original intent seem to be to harmonize border enforcement with existing law  in a way that benefited everyone. But what happened was that as the borders became less porous, migrants began seeking out for dangerous border crossings. Often these were in the high desert where risk of injury and death was higher, as the cost of crossing the border back and forth increased due to this danger, migrants were less likely to engage in cyclical migration but rather stayed in the United States and either send money home to Mexico or brought their families here.

This has profound implications for the current state of affairs. As each successive administration cracks down on illegal immigration, tightens the border, and militarizes the border patrol, it increases the risks and costs associated with crossing back and forth. Migrants still want to come to America, people are still claiming asylum, but illegal immigrants in the United States are persecuted and stay in hiding. Every indication is that the worst possible thing that could be done would be the actual construction of a wall.  In some ways, an analogy can be drawn to desire paths in public spaces. There is a natural flow to collective human behaviour. Civic planning and architecture does not always match, but human behaviour will always win out. People will continue to migrate and this will continue to be a problem.

Gladwell doesn’t say this, but it seems to me that the most rational and humane solution is a porous border. In a porous border, illegal immigrants are turned back when apprehended, but in a straightforward way. People are not apprehended and put into detention centers. Families are not charged with committing a misdemeanour offence and jailed prior to their hearings necessitating the removal of the children. In a porous border, there is still border security but the overall level of enforcement is lower.  In addition, a policy like this could benefit from increased access to green cards,  recognizing that many migrants wish to work in the United States for a few months. Unfortunately, no one in the Southwest (or anywhere else in America) is going to win an election with the promise of “Let’s make our border more porous and engage in lax border security.” That will not sell. But the evidence presented by the Mexican migration project and reviewed by Gladwell in his podcast suggests this would still be the most rational solution.

More Objective Research

This is one of those cases where we need more objective policy research, less political rhetoric. Has anyone asked an algorithm or computer model to determine the ideal level of border security? How much flow is tolerable? How does one balance economic detriment to having a relatively free flow of migrants with the costs associated with apprehension detention and deportation, and any associated criminal proceedings. The latter are expensive and human-resource intensive. Do to the risks of a porous border justify these expenses?

The thing is, these are computational problems. These are problems that demand rigorous computational analysis and not moralistic grandstanding about breaking the law for fears of drugs and criminals poring over the border.

The evidence seems to suggest that for decades, the relatively porous border had no ill effects on American society and was mutually beneficial to the US and to Mexican border regions. Though unintended, the slow militarization of the US-Mexico border restricted migration, made it more dangerous, which led to real costs illegal immigration thus necessitating a stronger more militaristic response, which creates a feedback loop. The harsher the enforcement the worse the problem gets.

The current administration has adopted the harshest enforcement yet, one that in my view is intentionally cruel, is a clear moral failing, and one that may be destined to fail anyway.

Artificially Intelligent—At the Intersection of Bots, Equity, and Innovation

This article was written in collaboration with my wife Elizabeth. We wrote this together and the ideas were generated during some of the great discussions we had during our evening 5k runs.

We all remember Prime Minister Trudeau’s famous response when asked about his gender equity promise for filling roles in the cabinet: “because it’s 2015.” And really, this call to action comes quite late in the historical span of modernity, but we’re glad someone at the highest levels of government in a developed nation has strongly proclaimed it. Most of us in Canada and likely around the world, were pleased to see Trudeau had staffed his cabinet with a significant amount of female leaders in important decision-making roles. And now, it’s 2017–a year that has been pivotal to say the least. Last Spring, Canada’s Minister of Science, Dr. Kirsty Duncan announced that universities in Canada are now required to improve their processes for hiring Canada Research Chairs and ensure those practices and review plans  are equitable, diverse and inclusive. The government of Canada’s announcement is a call to action to include more women and other underrepresented groups at these levels, and it’s essentially come down to ultimatum: research universities will simply not receive federal funding allocations for these programs unless they take equity, diversity, and inclusion seriously in their recruitment and review processes.

IMG_20161205_072820602When placed under the spotlight, the situation is a national embarrassment. Currently there is one woman Canada Excellence in Research Chair in this country and for women entrepreneurs the statistics are not much better. Women innovators in the industrial or entrepreneurial sphere are often left hanging without a financial net, largely as a result of a lack of overall support in business environments and major gaps in policy and funding. The good news is that change is happening now, and it’s affecting policies and practices at basic funding and policy levels. Federal and Provincial research granting agencies in Canada are actively responding to the call for more equitable and inclusive review practices within the majority their programs. The message is clear from the current Canadian government: get on board with your EDI policies and practices, or your boat won’t leave the harbour. But there’s always more work to be done.

The Robot Revolution

Combined with our pivotal political moment in history and on-going necessity for a level playing field for underrepresented groups, humans are situated at a crossroads of theory and praxis of human-machine interaction. The current intersection of human and machine certainly has critical implications for the academy, innovation, and our workplaces. It exposes the gaps to see what is possible, and we know the tools are here and must be harnessed for change. Even though we are literally living through mini “revolutions” each day as new technologies, platforms and code stream before our very eyes, humanity has been standing at this major intersection for a couple of centuries or more–at the very least, since the advent of non-human technologies that help humans process information and communicate ideas (cave paintings, the book, the typewriter, Herb Simon’s General Problem Solver). The human-AI link we need to critically assess now however, is how this convergence of the human-machine can work for women and underrepresented groups in the academy and entrepreneurial sectors in powerful ways. When it comes to creating more equitable spaces and providing women with the pay they deserve, we need to move beyond gloomy statements like “the robots are taking our jobs.” We must seek to understand how underrepresented and underpaid people can benefit from robots rather than running from them. And we must seek to understand why women in the academy, industry and other sectors haven’t been using the AI tools in dynamic ways all along. [Some are of course. As evidenced here. Two women business owners harnessed the power of technology to grow their client and customer base by sending emails from a fictional business partner named “Keith.” Client response to “Keith” seemed to do the trick in getting their customers and backers to take them seriously.]

Implicit Bias

In the psychology of decision making, a bias is usually defined as tendency to make decisions in a particular way. In many cases, the bias can he helpful and adaptive: we all have a bias to avoid painful situations. In other cases the bias can lead us to ignore information that would result in a better decision. An implicit bias refers to a bias that we are unaware of or the unconscious application of a bias that we are aware of. The construct has been investigated in how people apply stereotypes. For example, if you instinctively cross the street to avoid walking past a person of a different race or ethnic group, you are letting an implicit bias direct your behaviours. If you instinctively tend to doubt that a woman who takes a sick day is really sick, but tend to believe the same of a man, you are letting an implicit bias direct your behaviours. Implicit bias has been shown to also affect hiring decisions, teaching evaluations. Grants that are submitted by women scientists often receive lower scores and implicit bias is the most likely culprit.  Implicit bias is difficult to avoid because it is implicit. The effect occurs without us being aware of it happening. We can overcome these biases if we are able to be more aware that they are happening. But AI also offers a possible way to overcome these biases as well.

An Engine for Equity at Work

AI and fast-evolving technologies can and should be used by women right now. We need to understand how they can be harnessed to create balanced workplaces, generate opportunity in business, and improve how we make decisions that directly affect women’s advancement and recognition in the academe. What promise or usefulness do AI tools hold for the development of balanced and inclusive forms of governance, review panel practices, opportunities for career advancement and recognition, and funding for start-ups? How can we use the power of these potent and disruptive technologies to improve processes and structures in the academy and elsewhere to make them more equitable and inclusive of all voices? There’s no denying that the tech space is changing things rapidly, but what is most useful to us now for correcting or improving imbalances or fixing inequitable, crumbling, and un-useful patriarchal structures. We need a map to navigate the  intersection of rapid tech development and human-machine interaction and use AI effectively to reduce cognitive and unconscious biases in our decision-making; to improve the way we conduct and promote academic research, innovation and governance for women and underrepresented groups of people.

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Some forward thinking companies are using the approach now. For example, several startups are using AI to prescreen candidates for possible interviews. In one case, the software (Talent Sonar) structured interviews and extracts candidate qualifications and removes candidate’s names and gender information from the report. These algorithms are designed to help remove implicit bias in hiring by focusing on the candidate’s attributes and workplace competencies without any reference to gender. Companies relying on these kinds of AI algorithms report a notable increase in hiring women. Artificial Intelligence, far from replacing workers, is actually helping to diversify and improve the modern workforce.

Academics have seen this change coming. Donna Haraway, in her Cyborg Manifesto re-conceptualizes modern feminist theory through a radical critique of the relationship between biology, gender, and cybernetics. For Haraway, a focus on the cybernetic–or the artificially intelligent–removes the reliance on gender in changing the way we think about power and how we make decisions about what a person has achieved, or is capable of doing. Can we, for example, start to aggressively incorporate AI methods for removing implicit or explicit bias from grant review panels–or more radically, remove humans from the process entirely? When governing boards place their votes for who will sit on the next Board of Trustees, or when university review committees adjudicate a female colleague’s tenure file in the academy, could this not be done via AI mechanisms or with an application that eliminates gender and uses keyword recognition for assessing the criteria? When we use AI to improve our decision making, we also have the ability to make it more equitable, diverse and inclusive. We can remove implicit or explicit cognitive biases based on gender or orientation, for example, when we are deciding who will be included in the next prestigious cohort of Canada Research Chairs.

AI can, and will continue to change the way human work is recognized in progressive ways: recognition of alternative work during parental leaves, improved governance and funding models, construction of equitable budgets and policy, and enhanced support for women entrepreneurs and innovators. AI is genderless. It is non-hierarchical. It has the power to be tossed like a dynamite stick to disrupt ancient academic structures that inherently favour patriarchal models for advancing up the tenure track. Equalization via AI gives women and underrepresented groups the power to be fully recognized and supported, from the seeds of their innovation (the academy) to the mobilization of those ideas in entrepreneurial spaces. The  robots are in fact still working for us–at least, for now.

When is it OK to steal?

Cheap Fares

Several recent news items caught my attention over this holiday weekend. In the first, it was reported that Delta airlines sold many tickets at a ridiculously low fare, and will honor those ticket sales regardless (they may have no choice because of a federal law requiring truth in advertising for airlines). As word of the cheap fares spread on Twitter and Facebook, people flocked to Delta’s website to buy these cheap tickets, even as they were aware that the pricing was an error.  They were very cheap: “A roundtrip flight between Cincinnati and Minneapolis for February was being sold for just $25.05 and a roundtrip between Cincinnati and Salt Lake City for $48.41. The correct price for both of those fares is more than $400.” In essence, they took advantage of an error and got something for much less than market value.

People did not seem to mind, and viewed this is ethically defensible. Consider this sampling of comments after an NPR article about this event: “The published price is the published price. It’s not like the passenger hacked into the system. Come on folks!” or “How did this airline’s mistake turn into us being unethical for buying their tickets? Their normal prices are the only unethical part of this situation.” or “They change their prices minute-to-minute based on their hidden math. If that math turns out to be wrong, I’ll sleep just fine.”

So most people, it seems, would buy the ticket, would not feel bad, and would not feel that they had made an unethical decision. I will come clean as well. I would absolutely buy a pricing error ticket, even if I knew it was an error.

Wells Fargo Kills a Homeowner

The second item was posted on Facebook by a friend of mine. It seems that years ago, a simple typographical error by Wells Fargo bank created a series of events that ended up with Wells Fargo erroneously foreclosing on a home, even after they realized their mistake. They billed the owner for unpaid property tax (it was actually his neighbor that was behind).  In order to collect the back taxes, they doubled his mortgage payments and as a result, he fell behind in his mortgage, and so they foreclosed and sold his home. Incredibly, Wells Fargo admitted their own error, but rather than correct it, they sold his home anyway! Eventually, the owner literally died in court trying this fight this. Naturally, we are all incredulous. Wells Fargo knew it made a mistake, but foreclosed anyway. They are the epitome of a heartless, cruel corporation and this is all reminiscent of a bureaucratic dystopia like Brazil.

But at the core, are these events really that different?  In each case, a technical error caused the sale to happen. In each case, the items should not have been sold. There was never a real $25 fare to Salt Lake and back taxes were never really owed. In both cases, the buyer benefits and the seller suffers. Why are we almost all OK with Delta being screwed out of airline fare but deeply offended at Wells Fargo? It seems like these events should be equivalent. Wells Fargo should not have sold  the condo, and Delta should not be required to honor those fares.

Clearing the Shelves at Wal-Mart

One might argue that the Wells Fargo case is different, the error was discovered before the sale. And so these events are not equivalent. So a third news story might be a better example. A few months ago, a technical error allowed people on food assistance (food stamps) to use their benefits cards without a limit. The error was made by by Xerox, who runs the EBT program in many states. In Louisiana, customers at a Wal-Mart, realized that the cards had no limit, word spread, and they cleared the shelves. Police were actually called, though Wal-Mart (much like Delta) said they would honour the sales, as no laws were broken. Card users knew this was a result of an error. But unlike  the Delta case, in which people are nearly universally accepting of the cheap fares, the benefits card incident was widely condemned. Comments like “No matter how you cut it, it was theft and those who took advantage should be prosecuted!” or “This is absolutely disgusting and everyone who used one of those cards and “stole” stuff should go to jail and forever have their EBT benefits cancelled for life.”, were common in the news reports.

I’m left with the same questions. Why is it alright to steal a fare from Delta (paying $25 for a $400 fare is stealing $375 worth of air time from them) but it is absolutely not aright to steal from Wal-Mart. Both are big corporations. Neither will be hurt by this minor glitch, and any tiny bit lost revenue would be passed on to another consumer anyway. Does this dichotomy exist because the Delta shoppers were on-line whereas Wal-Mart shoppers were loading up in person? Does this dichotomy exist because the Delta shoppers were from all walks of life, but the Wal-Mart  shoppers were “welfare types”. Is it more OK for a savvy traveler to steal from Delta than a welfare bum to steal from Wal-Mart? Would we condemn the Delta ticket buyers if it were revealed that all were on public assistance?

I do not have a quick answer, though I feel like a properly controlled experiment might be in the works.

Thanks for reading, and thoughtful comments are welcome, of course.