Yes, computing belongs within social sciences, but...


WHO should study WHAT first, exactly?

Yes, computing belongs within social sciences, but... /img/trolley-problem-grandma-or-baby.jpg
WHO teaches to whom which human the car computer should hit?

Here is a synthesis, and a partial critique, of “Why Computing Belongs Within the Social Sciences”, where Randy Connolly argues that “the well-publicized social ills of computing will not go away simply by integrating ethics instruction or codes of conduct into computing curricula”:

Since computing is becoming progressively more entangled within society, its academic curricula must move away from engineering-inspired curricular models, and integrate concepts supplied by social science theories and methodologies.

Initially, computing studies introduced the way to think and act labeled as, among other things, algorithmic, or computational thinking. Eventually, it became common wisdom that everyone can, and above all should, benefit from thinking like a computer scientist.

In parallel, it was claimed, or passively accepted, that computing could “get” society without needing background in social theory, economics or psychology.

Today, computing is still widely believed to provide a privileged, methodologically superior set of techniques and approaches that can be applied universally.

This both academically arrogant, and short-sighted: computing would be immeasurably improved by supplementing its own with the methods, theories, and perspectives of the social sciences. Indeed, one could claim that not only would computing be improved by more social science, but that…

Computing today actually IS a social science

Social sciences are the academic disciplines that study human society, and human individuals in the context of society. One of the key insights (and values) of the social science of the past half century is its embrace of complexity: “methodological and theoretical pluralism is what defines both the social sciences in general, but also its subject, humans in social, political, economic, and cultural contexts”.

In natural and engineering sciences, instead, predictability of subjects can [justify] a single methodological approach for making and evaluating knowledge claims.

Computing, however, has a “social scientific nature” because it is deeply implicated in relations of power. These days, power relies on coercion much less than on persuasion (or on occulting data). Algorithms and automated decision and prediction systems are replacing the human agency built into our legal and political systems: our range of possible action will no longer be controlled by law, but instead be controlled by code.

Unfortunately, too many computing professionals (starting with Zuckerberg and other, similarly immature folks) still ignore all this, and see themselves only as problem solvers. Very few of them would think that they are also doing politics. But “In the future, how we perceive the world will be determined more and more by what is revealed to us by digital systems … To control these is the essence of politics.” (Problem is, when the kids in charge realize that this is the kind of toy they are messing with, they don’t know what to do)

Technologists carry a burden, but this reckoning will not happen unless [computing curricula] change.

Three Recommendations for Transforming Computing

Following these consideration, with which I almost completely agree, Connolly calls for a change of mentality that should happen through three recommendations:

Recommendation 1:Embrace other disciplines’ insight, rather than expect to just colonize them and “rely on pop-culture theories about inevitable technology-driven social change”.

For example, for anthropologists it is obvious that cultural differences and perceptions of otherness biases the observations of researchers. And, yet, in AI research, we are now only starting to recognize this fact because of an institutionalized blindness to the accumulated insights of a century of social research.

Recommendation 2: Replace some computing courses with social science ones: computing graduates need much more than knowing different algorithms for ethical trolley problems, often packed into one course, detached by all the others.

Recommendation 3: Embrace multidisciplinarity through faculty hiring.

OK, to change studies but… WHO should study WHAT first, exactly?

Connolly says many right things. One limit I see in the article is the implicit assumption, or acceptance, that this education should only happen at college level, that is only target an elite. Everybody should get it, as soon as possible.

Regardless of age, my main concern with his proposal, if I understand it correctly, is that it seems too focused on what programmers should study. It seems to give for granted that, since programmers occupied the driver seat when everybody was looking elsewhere, it is them who must and will remain in charge, and therefore the only solution is to educate them well.

Actual programming and software engineering are something else. But the social nature and impacts of something as powerful as computing must be understood by everybody, not just programmers. This issue comes out in comments to the article such as:

  • Finance too needs social sciences doesn’t it?”
  • “We do need our laws to catch up with our tech, aka get more computer science into social sciences… into everything”
  • “Non-CS disciplines need more courses about technology–especially politicians and business

Or, as I said last year, “it’s not maths and tech specialists who need Hippocratic Oath”.

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