NYU sociologist Mona Sloane, a member of the AIEI Board of Advisors, and Twitter director Rumman Chowdhury, refer to these as " narrative traps," cautioning decision-makers to be “mindful of the kind of pitfalls of the stories that we tell each other as we do our work and engage professionally with these topics. The resulting risk paradigms are not necessarily inclusive or comprehensive, and lack the ability to give voice to those less funding or power. "Some people’s altruism puts other people under their power," she writes.Īrguably, strategic philanthropies, often run by private individuals with their own particular visions and goals, generate potentially "objectionably hierarchical social and political relationships." Large sums of money can define questions and narratives. These attempts may result in "relational inequality"―those most affected have the least say, according to political theorist Emma Saunders-Hastings.
It may be to support value systems such as "long-termism” and “existential risk” which are themselves particular framings that prioritize certain values and are, again, contentious and contested― with good reason.īoth corporate and privately owned institutions play an ever increasing role in shaping what are tolerated as valid AI risks and the timeline of the ethical conundrums―a phenomenon that has previously been seen in other fields, including nuclear and bioweapons research.
But the current influx of investment is not designed to create something beautiful for the world, nor even to necessarily solve problems in the most appropriate way―it may be to keep tech company valuations and stock prices inflated, despite the shortcomings, risks, and failures of leaders to deliver on technologies after decades of promise. As a result, the composers of this era were some of the most prolific as far as creative music production the monarchs’ investments helped to add value for generations of music lovers. Wealthy companies are pouring enormous amounts of resources into technological solutionism, much like how during Mozart’s lifetime, German monarchs directed huge amounts of funding at composers. Such data-centric solutions can be flat-out dangerous when embedded prematurely in critical functions alongside humans who are ill-prepared to understand and work around the limitations of the algorithms and the problems associated with large datasets. During perilous times, when global stability is weakening and tension points are multiplying, there is a risk that the promise of what we can accomplish by machine learning and AI will supersede ethical considerations around known limitations. Far from the cutting edge of AI research, they merely involve bringing larger data sets and more computing power to bear on problems that could often be solved more cheaply and effectively by properly trained humans and investments in organizational culture. In truth, many supposed “AI solutions” are currently nothing more than corporate snake oil and pixie dust. An honest and scientific discourse on AI is frequently lacking. As a result of hyping the possibilities of the technology, the potential risks and limitations of technology are often under-communicated and poorly understood. This kind of magical thinking is not without a cost. Last year, for example, an EU Parliament document hyperbolically claimed that " AI can be thought of as the fifth element after air, earth, water, and fire." Not a small part of the exorbitant investment in AI can be traced back to magical thinking.
In the 1980s, data scientist Josef Weizenbaum warned about the " magical thinking" around technology, saying that the only people in awe were the people who misunderstood the technology.
DEUS EX MACHINA MOVIE MOVIE
Everyone leaves the movie comforted that technology has won the day. In so many sci-fi movies, the resolution of the plot is that of deus ex machina―literally, a "god in the machine." In these movie endings, a highly improbable development solves a seemingly intractable problem, leading to a happy ending, without reflection, or even reason.
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