Our embrace of data-driven services such as artificial intelligence and machine learning will have an unprecedented impact on our present and future. Meanwhile, regulation has not always evolved with emerging technology. If technological debates are not part of the public agenda, the social impact that will inevitably transpire will become a massive societal challenge.
For instance, will human-in-the-loop AI workers become a euphemism for “sacrificial workers,” meaning whenever “foolproof” technology provokes an accident, large or small, will the nearest human operator be blamed?
At the core of this challenge are algorithms. They need to be rigorously understood, framed and regulated as they become fixtures of people’s daily life and business activities. This includes an approach that’s daring in hypotheses, approaches and methodologies to appraise algorithmic impact and regulate for known unknowns.
Algorithms, and the data they process, play an increasingly important role in predictions, decision making and recommendations. Many already receive innocuous book recommendations, a more efficient route to a destination, or even a winning strategy for a game of Go or chess.
However, what about algorithmically enhanced decisions that determine one’s college admittance, loan approval, or job prospects? Even though the public largely believes that machines are neutral arbiters – entities that always make the right decision or see patterns that our human minds can’t or won’t. But are they really neutral? Or are algorithms a way to amplify and extend the biases and discrimination that is prevalent in society?
Major advances in artificial intelligence and machine learning have encouraged corporations to rely on big data and algorithmic decision making with the presumption that such decisions are efficient and impartial.
However, the truth is that algorithms are social constructs as much as mathematical calculations. As with any other technology, they capture and reproduce social dynamics, but these social dynamics often become entangled in obscure technical debates.
An algorithmic audit is a novel way to vet and rigorously frame bias and fairness as well as understand what algorithms are and the role they play in our society. This results in a greater accountability in algorithmic design and implementation,
As algorithms play a role in hiring, credit scoring, even setting ambient temperature in office buildings, they’re mysteriously and inevitably shaping our lives in both big ways and small. If algorithms are becoming key to so many day-to-day activities, the need to grasp its impact emerges as an urgent matter. This is, however, no easy task.
In our next post, we’ll frame what algorithms are and the roles they play and why it requires a multidisciplinary approach.