Philosophy and computing in the age of data science
In its next issue the Economist will feature an article on the key role that machine learning and Big Data have in reaching scientific breakthroughs in biology. This is just the latest article stressing the opportunities that come with machine learning, Big Data, data science and, more in general, computing. I believe that it is of the utmost importance that these opportunities will not be missed and also that philosophy has a central role to this end.
In my first editorial letter for Minds and Machines, I argued that philosophy and computing have often been related in the history of human culture and that this relation has grown to define an entire area of philosophical enquiry. For the past decade we thought of this area as delineated by two Cartesian axes: conceptual and methodological. On the conceptual axis we find the deep philosophical questions concerning the concepts of information, computation, algorithms, cognition, intelligence, and language. On the methodological axis we find philosophical research developed through computer science methods, formal methods and levels of abstraction being notable examples.
However, something is missing from this picture. As the information revolution unveils its full potential, we come to realise that computing has changed our daily practises and, more than that, it has provided us with new lenses to understand our environment and with new means to shape it—consider for example the impact of machine learning, Big Data, data science, and virtual reality on scientific research. These changes prompt new philosophical enquiries, which do not belong to the conceptual or the methodological axes, rather they are located on a third Cartesian axis, the contextual one.
Philosophical enquiries located along the contextual axis face new, pressing problems, concerning the way we produce scientific knowledge (philosophy of science), the nature of this knowledge (epistemology, and of the tools we use to produce it (philosophy of computing, philosophy of mathematics, and philosophy of statistics), as well as their ethical implications (ethics). It is with the contextual axis in the picture that the area of philosophy and computing is fully delineated and its importance becomes evident.
Philosophical analyses change over time to reflect their context; the scientific knowledge on which societies rely and the principles, both ethical and cultural, that shape them. The value of philosophy rests in this dynamism. Philosophy remains meaningful insofar as it changes to address the needs of the social, cultural, and historical context to which it belongs. A meaningful philosophy is a philosophy of its time. Together the three Cartesian axes ground philosophy in the information age. They embed it in its time and, in doing so, they contribute to enhance the value of philosophical analyses.
As new milestones have been achieved in cognitive science, artificial intelligence, and quantum computing, philosophical analyses resting on the conceptual and methodological analyses remain valid and important to pursue. At the same time, it is crucial to focus also on those philosophical enquiries located along the contextual axis. These will further our understanding of the reality in which we live and, by doing in so, they will contribute to shaping a better one for current and future generations. The alternative is too dangerous, as it may make philosophy and computing an aseptic, if not an uninteresting, area of research.
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