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Category: algorithmic bias

The ethics and governance of AI

The ethics and governance of AI

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From the Harvard Law Bulletin, summer 2018, “The morality in the machines.” “Its goal: to research and brainstorm new legal and moral rules for artificial intelligence and other technologies built on complex algorithms.[…] ‘Companies are building technology that will have very, very significant impacts on our lives,’ says HLS Clinical Professor Christopher Bavitz, faculty co-director of the Berkman Klein Center and another leader of the AI initiative’s research. ‘They are raising issues that can only be addressed if you have…

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A dive into the black waters under the surface of persuasive design

A dive into the black waters under the surface of persuasive design

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A Guardian article last October brings the darker aspects of the attention economy, particularly the techniques and tools of neural hijacking, into sharp focus. The piece summarizes some interaction design principles and trends that signal a fundamental shift in means, deployment, and startling effectiveness of mass persuasion. The mechanisms reliably and efficiently leverage neural reward (dopamine) circuits to seize, hold, and direct attention toward whatever end the designer and content providers choose. The organizer of a $1,700 per person event…

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Gender role bias in AI algorithms

Gender role bias in AI algorithms

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Should it surprise us that human biases find their way into human-designed AI algorithms trained using data sets of human artifacts? Machine-learning software trained on the datasets didn’t just mirror those biases, it amplified them. If a photo set generally associated women with cooking, software trained by studying those photos and their labels created an even stronger association. https://www.wired.com/story/machines-taught-by-photos-learn-a-sexist-view-of-women?mbid=nl_82117_p2&CNDID=24258719

TED Talk and PJW Comment

TED Talk and PJW Comment

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TED talk of possible interest: http://www.ted.com/talks/zeynep_tufekci_we_can_t_control_what_our_intelligent_machines_are_learning?utm_source=newsletter_weekly_2016-10-22&utm_campaign=newsletter_weekly&utm_medium=email&utm_content=talk_of_the_week_swipe Comment I posted there: Here is an interdisciplinary “moon-shot” suggestion that we should at least start talking about, now, before it is too late. Let’s massively collaborate to develop a very mission-specific AI system to help us figure out, using emerging genetic editing technologies (e.g., CRISPR, etc.), ideally how to tweak (most likely) species-typical genes currently constraining our capacities for prosociality, biophilia, and compassion, so that we can intentionally evolve into a sustainable species….

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