Category Archives: Academia

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.

Does This Project Bring Me Joy?

 

I have too many research projects going on.

It’s great to be busy, but I’m often overwhelmed in this area. As a university professor, some of my job is well defined (e.g. teaching) but other parts not so much. My workload is divided into 40% research, 40% teaching, and 20% service. Within each of these, I have some say as to what I can take on. I can teach different classes and volunteer to serve on various committees. But the research component is mine. This is what I really do. I set the agenda. I apply for funding. This is supposed to be my passion.

So why do I feel overwhelmed in that area?

I think I have too many projects going on. And I don’t mean that I am writing too many papers. I’m most certainly not doing that. I mean I have too many different kinds of projects. There are several projects on psychology and aging, projects on the brain electrophysiology and category learning, a project on meditation and wellbeing in lawyers, a project on patient compliance, a project on distraction from smartphones, plus 4-5 other ideas in development, and at least 10 projects that are most charitably described as “half baked ideas that I had on the way home from a hockey game”.

Add to this many projects with students that may not quite be in my wheelhouse, but are close and that I’m supervising. And I’ll admit, I have difficulty keeping these things straight. I’m interested in things. But when I look at the list of things, I confess I have a tough time seeing a theme sometimes. And that’s a problem as it means I’m not really fully immersed in any one project. I cease to be an independent and curious scientist and become a mediocre project manager. And when I look at my work objectively, more often than not, it seems mediocre.

Put another way, sometimes I’m always really sure what I do anymore…

So what should I do about this, other than complain on my blog? I have to tidy up my research.

A Research Purge

There is a very popular book called “The Life Changing Magic of Tidying Up“. I have not read this book, but I have read about this book (and let’s be honest that’s sometimes the best we can do). The essence of the approach is that you should not be hanging on to things that are not bringing you joy.

Nostalgia is not joy.

Lots of stuff getting in the way is not joy. And so you go though things, one category at a time, and look at each thing and say “does this item spark joy“? If the answer is no, you discard it. I like this idea.

If this works for a home or a room…physical space…then it should work for the mental space of my research projects. So I’m going to try this. I thought about this last year, but never quite implemented it. I should go through each project and each sub project and ask “Does this project bring me joy?” or “Is there joy in trying to discover this?” Honestly, if the answer is “no” or “maybe” why should I work on it? This may mean that I give up on some things and that some possible papers will not get published. That’s OK, because I will not be compelled to carry out research and writing if it is not bringing me joy. Why should I? I suspect I would be more effective as a scientist because I will (hopefully) focus my efforts on several core areas.

This means, of course, that I have to decide what I do like. And it does not have to be what I’m doing. It does not have to be what I’ve done.

The Psychology of the Reset

Why do we like this? Why do people want to cleanse? To reset. To get back to basics? It seems to be the top theme in so many pop-psych and self help books. Getting rid of things. A detox or a “digital” detox. Starting over. Getting back to something. I really wonder about this. And although I wonder why we behave this way, I’m not sure that I would not find joy in carrying out a research study on this…I must resist the urge to start another project.

I’m going to pare down. I still need to teach, and supervise, and serve on editorial boards, etc: that’s work. I’m not complaining and I like the work. But I want to spend my research and writing time working on projects that will spark joy. Investigating and discovering things that I’m genuinely curious about…curious enough to put in the hours and time to do the research well.

I’d be curious too, to know if others have tried this. Has it worked? Have you become a better scholar and scientists by decluttering your research space?

Thanks for reading and comments are welcome.

Inspiration in the Lab

I run a mid sized cognitive psychology lab: it’s me as the PI, 2 PhD students 3 master’s students and a handful of undergraduate honours students and RAs. We are a reasonably productive lab, but there are times when I think we could be doing more in terms of getting our work out and also coming up with innovative and creative ideas.

Lately I’ve been thinking of ways to break out of our routines. Research, in my opinion, should be a combination of repetition (writing, collecting data, running an analysis in R) but also innovation where we look at new techniques, new ideas, new explanations. How to balance these?  Also, I want to increase collaborative problem solving in my lab. Often a student has a data set and the most common process is the student and I working together, or me reviewing what she or he has done. But sometimes it would be great if we’re all aware of the challenges and promises of each other’s work. We have weekly lab meetings, but that’s not always enough.

What follows are some ideas I’d like to implement in the near future. I’d love to hear what works (and does not work) from other scientists.

An Afternoon of Code

We rely on software (PsychoPy, Python, R, and E-Prime) to collect behavioural data. We have several decent programs to run the experiments we want to run, but that is often a bottleneck, and all of us sometime struggle to translate ideas into code. One way to work on this might be to have a coding retreat or an afternoon of coding. We all agree to meet in my lab and we work on shared task or designing a paradigm that we’ve never used before. I’d put up a prize for the first student to solve the problem. As an example, I’m looking to get a version of the classic “weather prediction task“. We might agree to spend a day working on this, maybe each on our own program, but at the same time so we can share ideas.

Data Visualization and Analysis

Similar to the idea above, I am thinking of ways to improve our skills on R-Studio. One idea might be to have a set of data from the most recent study in our lab and we spend a day working together on R-Studio to explore different visualizations, techniques for parsing, etc. We each know different things and R allows for so much customization, but it would be helpful to be aware of each other’s skill set.

Writing at the Pub

Despite some of its limitations, I’ve been using Google Docs as a way to prepare manuscripts for publication. It’s not much worse than Word but really allows for better collaborative work and integrates smoothly with #Slack. With the addition of Paperpile, it’s a very competent document preparation system. So I thought about setting aside a few hours in the campus pub, bring our laptops, and all write together. Lab members that are working together on a paper can write simultaneously. Or we might pick one paper, and even grad students who are not authors per se would still be able to help with edits and idea. Maybe start with coffee/tea…then a beer or two.

Internal Replications

I’ve also thought about spending some time designing and implementing replications of earlier work. We already do this to some degree, but I have many published studies from 10 or more years ago that might be worth revisiting. I thought of meeting once every few month with my team to look at these and pick one to replicate. Then we work as a team to try to replicate the study as if it were someone else’s work (not ours) and run a full study. This would be done along side the new/current work in our lab.

Chefs learn by repeating the basic techniques over and over again until they master them and can produce a simple dish perfectly each time. I can think of no reason not to employ the same technique in my lab. I think the repetitive, inward focused nature of a task like this might also lead to new insights as we rediscover what led up to design a task or experiment in a certain way.

Conclusion

I am planning on taking these ideas to my trainees at a one of our weekly lab in the next few weeks. My goal is to just try a few new things to break up the routine. I’d welcome any comments, ideas, or suggestions.

Taming My Distracted Mind

There is mounting evidence that digital devices, screens, smartphones are a real roadblock to productivity. The very tools that are supposed to make us more productive might be robbing us of that ability.

The Modern Worker

I’m a psychology professor at a large research institution. This means that although I do spend some time teaching in a large lecture hall, mostly I’m in my office writing, reading, doing email, attending meetings, and planning…that is, spending my time like many other modern workers. I’ve been at this for a while and I can still recall a time when not everyone had an email address, when research articles had to be printed, when submitting my work to a journal meant actually mailing four identical copies of the manuscript to the publisher. But nearly all of that is now done on line. I sit at my desk to do email, to read, to analyze data, to access research papers, to grade assignments, comment on student work …everything. And lately this has expanded to me writing and managing email at home, at breakfast on my phone, reading email in a faculty meeting on my phone, in bed on my phone…in the bathroom on my phone. An really…why am I doing my work in the bathroom?

What’s more, everything is being carried out on a device or a browser that is also used for recreation media consumption and social media. I read news, play games, and watch baseball games on my laptop. I watch sports on my laptop and tweet about the game at the the same time.

What this means is that my workstation is essentially also a playstation.

A Tired Mind

Lately I’m finding that a week of desk/computer work leaves my mind feeling like mush. Much more cognitive fatigue that there used to be. I’m less able to focus on my work. I can’t read the whole way through a paper. I’ll start and email and write two lines and then my attention wanders. It did not used to be this way, and it’s not just because I’m getting older (I’m a few weeks shy of 47). I think my work habits have begun to tire me out.

Meditation does help in this regard…I can meditate for 10–15 minutes with little difficulty. And running helps too: I can run for an hour without getting bored and feel refreshed (not tired)

But the minute I’m at my desk I slide right back into the habit of having 10 browser tabs open…each one vying for my attention.  No matter what I try, the second I sit down at my university office or home office to write, I lose my ability to concentrate on my work. It starts with email, and then 10 minutes of local news, maybe twitter….some more email. And back and forth and them I’m still working on the same email.

Some remedies

I’ve started taking steps this week to create some “digital distance” at work. Small habits to try to improve my work experience. None of this is scientific: I’m just trying to retrain. And I’m not so much interested in being more productive…just less tired.

  1. I’m printing more and screen reading less. This goes for articles, student work, and editing my own work. (don’t worry: I’m recycling the paper by printing on the back of other used paper!)
  2. This is big one: After many years of running everything through a browser and Gmail, I’m switching back to an actual email client (Spark Mail App for mac). That way, when I decide to do email, I’m ONLY doing email and not tempted to read FB, Twitter, news, etc. in another tab. Gmail or Outlook webmail was killing me for that because “hey you already have Chrome open, just leave a tab open for twitter”. So Chrome is closed when I’m responding to email.
  3. My lab and my graduate students are now on Slack (not email) so that when I’m doing project management, research planning, and advising, I can concentrate on that and nothing else. I close can Chrome and email
  4. I’ve turned all the notifications off on my smart phone, except texts/calls from my wife & kids, and their school.
  5. No posting to social media in the morning, because I’ll just be thinking about whether not there are hits. This is another big one. I’ll post something at breakfast or comment and then keep checking.I’ve already completely deactivated Facebook to make this even easier. My students and I are even carrying out a research study on this specific topic (more detail on that later..when the data are in).

I’m curious if others are finding similar things. Do you think that your productivity has waned? Do you think that working all day on a screen is reducing your ability to concentrate? Have you taken steps to correct this or retrain your mind? I’d be interested in hearing.

Almost no one reads my work. Should I care?

I recently read an article that has been going around social media in which the authors argue that basically no one is reading academic journals. They argue that in order to be heard, and in order to shape policy, professors and academics should be writing Op-Eds.

The article, which I’ve linked to here,  should be read with a few caveats. First of all, the authors suggest that the average academic paper is read in total by about 10 people. They provide no evidence or information about how they arrived at that estimate. Second, they are writing from the standpoint of social science and political science. In other words, the results may not apply to other disciplines. That said, I believe there are many reasons to take their idea seriously.

There are too many articles published every year.

There are so many scientific and academic journals operating right now. For example, the popular journal PLoS ONE  published 31,500  articles in 2013… That’s 86 articles a day.  In 2014, the published even more….33,000 articles. Only one of them was from my lab.  Now I happen to think that this particular article was a really good paper. It was based on my student Rachel’s master’s thesis. But it’s only one of over 30,000 articles that year. According to the statistics on their own site, there were about 1400 views of our article. So far it’s been cited twice.  Is that good? Is that enough?  Should I care? After all, it’s only one paper of many that I have published in the last few years

This is only the tip of the iceberg. As I said, this is one journal. There are other large journals like PLoSONE.  And there are many, many smaller journals with limited output. But still, it’s estimated that this year alone there will be over 2 million articles published.  Even if you assume that within your own field, it’s only a few thousand every year, finding the ones that matter can still be a problem. If you use Google scholar (and I do) to research, you may have noticed that it  it tends to place heavily cited articles at the top of the search. This is good, because it gives you a sense of which articles have had the most impact in the field. This is bad because the first thing you see is the same article that everyone else has cited for the last 20 years. Unless you take the time to adjust your search, you are not going to see any of the new work.

And as if this isn’t problem enough, there have been widely reported problems with the academic publishing world. For example some journals have even had to withdraw articles, many articles, when it was revealed that they were entirely computer-generated gibberish.  There are also hundreds and hundreds of so-called “predatory” journals in which the peer review is nonexistent, standards for publication are very low, and the journals operate solely to make money publishing papers that otherwise wouldn’t be published. You can see a list of these predatory journals here.  Even journals published by well-known companies have had difficulty recently. In some cases, editors have been accused of accepting articles with little or no to review.

Why do we do this?

I cannot speak for other academics, but within my field and for me, the reason is simple. It’s my job. As a professor in a large research institution, part of my job is to carry out scientific research, and publish the scientific research in peer-reviewed journals. Publishing papers in peer-reviewed journals was necessary for me to obtain tenure. It is necessary for me to be able to compete for federal research dollars. Other forms of communication can help in terms of getting the message out, but as it stands now, publishing a popular article, a textbook, a Op-Ed, a newspaper article, or even a popular blog essentially does not count. I might as well be doing that on my own time. Which, I suppose I am.

So in essence, we have a designed and embraced system that rewards publications in one format and does not reward publications in other formats. Unfortunately, the format that is rewarded is one in which almost no one outside of the immediate field will ever read.

What do we do about this?

I am not entirely sure what to do about this, but I do believe that it is a real problem. I’m not suggesting that scientists and academics abandon publishing in academic journals. In fact, I still think that’s exactly where primary research belongs. As long as the peer review is being carried out properly, editors are behaving properly, and editorial standards are high, this is exactly where you want your best work to appear. I also don’t want it to be the case that scientists and academics begin pursuing popular media at the expense of academic publishing.

What I would like to see, however, is an appropriate balance. It might be time for internal performance review committees and promotion and tenure committees to broaden the scope of what counts as scientific, academic, and scholarly contributions. This will provide some incentive for researchers to publicize their work. At the very least, researchers should not be penalized  for attempting to engage the public in their research. A successful research program is one that publishes in different outlets and for different audiences. We do this in my department, we work with the local public library, for example, to engage in popular science topics in psychology.  Our research communication office works long and hard to publicize and promote research. However, much of this is still considered to be secondary.

Another possibility, one that is suggested by the editorial staff at PLoSONE,  is for individual researchers to publicize their own work.  Researchers should share and Tweet their research as well as others.  And there are other formats, Google+, for example hosts a large scientific community that publicizes research, shares research, and even organizes virtual conferences. I’ve taken part in some of these, and they can be an effective way to share your work.

In the end, I wonder if we should all slow down, work more carefully, and think long and hard about the quality of our research versus the quantity of our publication output.  Otherwise, I think there is a real concern that the signal will be completely drowned out by the noise.

The Fine Print in the Syllabus

The end of July brings the realization that that I’ll be teaching graduate and undergraduate courses again in the fall, and that I need to prepare readings, lectures, and an official course outline for each course. In addition to being distributed to students on the first day of class, these outlines are archived and publicly available on the web. For example, here is the outline for the summer distance course that I am teaching this year . Here is the outline from the last time I taught the Introduction to Cognition course. My graduate courses use a similar format, and here is the outline from last fall’s graduate seminar on cognition. As you can see, there is a lot of information about the course, but also a lot of slightly silly stuff directing them to websites about other policies.

Fine Print

Every year, when I send these course outlines to the department’s undergraduate coordinator, I am informed that I have used the wrong template or have forgotten something.

For example. Last year, I forgot this:

“Computer-marked multiple-choice tests and/or exams may be subject to submission for similarity review by software that will check for unusual coincidences in answer patterns that may indicate cheating.”

Do the students need to know this up front? Is it not enough that we tell them not to cheat? Can they file an appeal if they were caught cheating and did not know that I was going to check ?

Not So Fine Print

Every year the list of non academic information that is required gets longer and longer. For example, this year I forgot to include a mental health statement. According to the university, I need to include the following statement in all course outlines:

“If you or someone you know is experiencing emotional /mental distress, there are several resources here at Western to assist you.  Please visit:  http://www.uwo.ca/uwocom/mentalhealth/ for more information on these resources and on mental health.”

I think this is a very strange thing to have in a course outline. It has nothing to do with my class. Surely students already know about non academic services, like mental health services?  And why stop there, maybe I should also consider a referral to the student health services if they or someone they know is experiencing a pain in their foot? Or to the gym if they are experiencing weakness in the upper torso? Or to a cooking class if they are malnourished. We have not yet been asked to issue “trigger warnings”  but I know that’s probably coming…

What is the intent here? I’m not suggesting that student not be informed of all the options available to them in terms of university life. I just wonder how relevant it is to the course outline. I id not think this kind of information belongs in my course outline.

Is it about control?

I think much of this is about the university exerting top down control. Requiring a series of statements for each course outline is a subtle power play. Academics sometimes like feel immune to the “TPS report” mentality, but we get it, and it gets worse each year.

In 2003, when I began teaching at Western, I created a syllabus, handed it out, taught the class, turned in the grades. Now, 11 years later, I use information from an official template for the syllabus, I send it for “approval” by the undergraduate office (it might be sent back), I sent it to IT to be posted, I  teach the course, I approve alternative exam dates at the request of the academic counsellor, when I turn in the grades, these are checked also to make sure they are not too high or too low. Ten years ago we had a chair… Now we have a chair plus 2 1/2 associate chairs (I was one of them for 4 years). Ten years ago, departments ran nearly every aspect of their own graduate programs, Now we have a central authority that has control over how exams are run, the thesis, and even the specific offer of admission. The letter that we write to students to offer admission to our graduate program is from a template, and any changes must to be approved. This letter gets longer and more confusing each year. It’s our TPS report. One of many TPS reports.

University, Inc.

The university is a business. I know it, everyone knows it.

Every year, we are informed  that we need to meet targets for enrolment, to put “bums in seats”. We are required to continually be seeking external funding and grants, to teach courses that will have appeal to student registered in different programs, to attach more graduate students. We’ve been asked to “sex up” the title of a course to see if more people will sign up. We now need to report on “internationalization” activities. That’s a buzzword, folks. We’re doing buzzword reports.

I’m not naive, I know the pressures. I’m just disappointed. And worried that it’s getting worse each year.