Facets: Issue 29

January 7, 2017

The End of Tech Optimism

Victor Luckerson
Apple, Alphabet, and Microsoft all have a larger market cap than Exxon Mobil. It’s past time we started treating them with the same level of skepticism.

In the blink of an eye, a handful of Silicon Valley companies have seized control of the digital world. According to Luckerson, startups' breakneck development has combined with human fallibility, and the casualties are the optimism and trust of the public. Technology can still change lives, but our outlook on those who build that technology and the problems they solve must change considerably in today's sociopolitical climate.

Tech, AI, Diversity, and What to Do About It in 2017

Lolita M Taub
AI interactions and feedback will be highly reflective of its creators, the data it uses, and the leaders in the space.

Artificial intelligence is billed as one of tech's next great challenges. However, the companies creating this new technology aren't diverse ones; any artificial intelligence they build will reflect that. Bias can be amplified, making the lives of marginalised people even more difficult as a result. By telling the story of her journey into the industry, Taub describes how artificial intelligence (and tech in general) can only achieve its goals if it is built by the diverse community that it will serve.

Masculinity and Machinery: Analysis of Care Practices, Social Climate and Marginalization at Hackathons

Gloria Lin
Why enter a space and contribute to its production if it tells you implicitly and explicitly that you will not be taken seriously?

Despite claims of inclusivity, hackathons still have a long way to go before everyone feels welcome. Gloria Lin describes how hackathon environments become exclusive and damaging— with homogeneous organisation teams, lack of attention to the needs of diverse attendees, and the rewarding of sexist work among other factors. She proposes hackathons start over, with transparency and diverse organisation. Events with these foundations would produce work which affects everyone, not just some of us, in a positive way.

The Algorithmic Justice League

Understanding Algorithmic Bias

This collective aims to identify and mitigate algorithmic bias and highlight the need for justice and inclusion in machine learning technologies. Its founder, Joy Buolamwini, uses her personal experience as a springboard, after having to wear a white mask because facial recognition software couldn't detect her bare face. Currently, the Algorithmic Justice League's efforts centre around monitoring bias in existing software, with a view to making future technologies more inclusive, from the ground up.

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