Communications of the ACM,
Vol. 63 No. 8, Pages 54-59
On October 23, 2008, Alan Greenspan, the Chair of the U.S. Federal Reserve, was testifying before Congress in the immediate aftermath of the September 2008 financial crash. Undoubtedly the high point of the proceedings occurred when Representative Henry Waxman pressed the Chair to admit "that your view of the world, your ideology, was not right," to which Greenspan admitted "Absolutely, precisely."17 Fast forward 10 years to another famous mea culpa moment in front of Congress, that of Mark Zuckerberg on April 11, 2018. In light of both the Cambridge Analytica scandal and revelations of Russian interference in the 2016 U.S. election, Zuckerberg also admitted to wrong: "It's clear now that we didn't do enough to prevent these tools from being used for harm. That goes for fake news, foreign interference in elections, and hate speech, as well as developers and data privacy."15
As far as mea culpas go, Greenspan's was considerably more concise, but also much more insightful as to the root problem. Greenspan admitted the problem was not due to misguided user expectations, or to poorly worded license agreements, or to rogue developers. Instead he recognized the problem lay in a worldview that seemed to work for a while ... until it didn't. In the immediate after-math of the financial crisis, there were calls for reforms, not only of the financial services industry, but also within universities, where it was thought that unrealistic models and assumptions within economics departments20 and business schools11 were also responsible for inculcating a worldview that led to the crisis. It is time for us in computing departments to do some comparable soul searching.
This is a really interesting paper! The provocation raised by the author must be taken seriously. Of course, Computer Science is not a humanistic discipline, but it is also true that digital technologies are now pervasive and their actual (not potential) impact is enormous both in positive and negative ways. The central point of the article, if we interpret it well, is the invitation to incorporate in the training of those who design computing technologies concrete knowledge and skills to manage this responsibility. Since the 1980s, Human-Computer Interaction has recognized and valued these interdisciplinary aspects: methodologies and approaches of humanistic disciplines have been used, but it is undoubtedly a discipline of Computer Science in its own right, so much so that its major conferences are organized with ACM.
Just a few weeks ago, the Italian chapter of the ACM Special Interest Group on Human-Computer Interaction (SIGCHI Italy) organized in collaboration with a National Laboratory of Artificial Intelligence and Intelligent Systems (CINI AIIS) a workshop to discuss a curriculum for teaching HCI in BSc and MSc degrees in Artificial Intelligence (http://sigchitaly.eu/en/hci4ai-syllabus/). The spirit was precisely the one suggested by the author: "We need to do more to fully educate our computing graduates than simply teach them deontological vs. utilitarian algorithms for ethical trolley problems." Soon we will publish a report on the results, still preliminary, of this activity that we consider important for future generations of Italian computer scientists. Meanwhile, we thank the author for pointing out this interesting perspective!
Maristella Matera (Politecnico di Milano, Italy) and Massimo Zancanaro (University of Trento, Italy), president and vice-president of the Italian Chapter of ACM SIGCHI.
Jesse De Pagter
Great article, the only thing I was missing a bit from my perspective as someone coming from the social sciences, is a 4th recommendation. Namely that the qualitative social sciences need more computing courses. So this is kind of a reversal of point 2: to replace some social science courses with computing ones. In my experience, especially social science fields that are more qualitative (vs. quantitative) often still lack this type of courses. I think this will help immensely to fulfill recommendation 3 (Embrace multidisciplinarity through faculty hiring). My hope is that this would increase the understanding among different fields, since we would acquire an increase in understanding of each other's methods, habits, thinking patterns etc.
My career in HCI sent me down a path of embracing the social sciences.
Lots of us in industry who are practicing User Experience have been embedded in social sciences for decades, required by the work.
It would great for us UX practitioners if more CS faculty joined us. We are waiting!
It is true that there have been an increased number of computing applications in our social lives--especially web applications and smartphone apps. However, this trend has not been limited to the social sciences or social aspects of our civilization. Digital transformation is happening in almost all disciplines and industries. Be careful that you are not falling victim to the availability bias. Congressional testimonies of tech CEOs are common in the news and this could lead some of us to believe that, there is a problem in computer science education. However, tech CEOs are not computer scientists, and if they were at one time they are definitely no longer in that role.
I agree with Jesse de Pagter. Non-CS disciplines need more courses about technology--especially politicians and business people. When the radio and television became popular, we didn't require physicists and electrical engineers to take more social science courses. We created new disciplines for broadcasting and media.
Outside of academia and in the IT industry, I've seen competent people with degrees in business, communications, or philosophy become mediocre business analysts (or product managers) because they lacked understanding of technology and software development. IT organization were complacent about this problem because the demand for IT workers was so high. Nowadays, there are plenty of certifications available for business analysis, product management, and project management. Similarly, I'd rather see a social sciences certification (or minor) than reducing the amount of CS in the core CS curriculum.
finance too needs social sciences doesn't it?
I stood in line to apply for Aeronautics Engineering degree in 1995, at a South Indian University and having noticed a mile long line in the counter next to me I wondered a bit and changed lines to apply, get admitted and graduate a Computer Science Engineering degree at age 21. And till I discovered economics as a subject in a pre-lude to my MBA ambitions at 27 I never could explain the sting I felt when the software I and my team members wrote was putting some well mannered and ultra kind middle age woman (mostly) in Tokyo's back office operations floor of a financial services firm.
That context was needed to bring me to my question -
DCF analysis - the holy grail (besides Black Scholes maybe) of much of finance (or excel based work in many mainstream finance till machines/HFT etc took over) has an assumptions sheet that serves as a pillar to pretty much every model ever built. These assumptions are drawn upon from various facets of life aka in my humble opinion social sciences.
So doesn't finance needs more social sciences?
While I more than agree and believe in the core argument of the author that more needs to be done in educating those who design the algorithms that are now turning to impact, control parts of economy governance, politics and society at large, wasn't that true at all times and disciplines?
So where does that leave us with the - educate the young more or educate to be all rounded - in an overworked school system that insists on teaching everyone everything through a cirrculum and means set ages ago and insisted on being ground into over a really really long time (age 6-18) as a minimum mandatory?
my guess is that nothing short of an education system redo right from kindergarten will address the current or near future needs let alone an economy where bi-ped humanoids and quantum computers will eat away more jobs than we can create as they change the fundamentals of labor market where we, humans, spend 18 years to add one more 'human resource' to the market while a machine (human like or more intelligent!) can be made by a 'copy paste' in an instant adding the same 'resource' to the market.
while we can't teach everything to everyone but as we try and do teach much to many we do need our laws to catchup with our tech aka get more computer science into social sciences into everything rather as computing or rather information processing is what we humans did/do as we turned to thought.
we just need to realize that we are replicating that very thought now, outside our bodies and at a scale unimaginable biologically.
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