Brett Wallace (2018)

Critic: Brett Wallace

From warehouse robots to autonomous cars, advancements in robotics and artificial intelligence enter our news feeds everyday. It seems every company is building some form of AI, real or imagined, into its strategy and products. Spectacular Hollywood narratives envision impending doomsday scenarios in which we encounter the singularity or a superintelligence turned against humanity.

The hype surrounding human productivity and singularity through AI, however, is a distraction from the impact that AI and robotics are already having for workers today. A recent report conducted by the McKinsey Global Institute last November found that about half of the work activities people perform could be automated with the current machine-learning algorithms underpinning AI. The workforce is unprepared and untrained for the AI world. Furthermore, those algorithms underpinning AI are critically flawed. Challenges such as these are contributing to marginalization and inequality for workers.

When it comes to the algorithms themselves, Kate Crawford, co-founder of AI Now, noted at a recent MoMA R&D Salon that if you do a search for CEO in any search engine, โ€œyouโ€™ll find a lot of images of white men in suits.โ€

โ€œDepending on which way the algorithm is blowing that day," Crawford continued, "the first woman that youโ€™ll see is, quite often, CEO Barbie.โ€ 

Here's another example of an at-best ill-designed algorithm: When MIT professor Joy Buolamwini was researching facial detection software, she noticed a problem: the software didn't detect her face. The algorithm had not been programmed to recognize a variety of skin tones. The โ€œcoded gaze,โ€ as Buolamwini calls it, was biased toward the predominantly white images fed to the algorithm.

Bias in coding is downstream from the systemic bias in our academic, government, and corporate institutions. Depending on who gets to make the rules, AI could sustain or exacerbate these systematic biases.  This is certainly a question to pose to the large four or five technology firms that are leading the development race of AI.

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