How Games Will Play You

What happens in games can have very real repercussions for the world outside them, particularly as modern machine learning methods give us the ability to infer so much about the person behind the keyboard or joystick. When we play games, we may not be aware that we are revealing information about ourselves. We are letting the game spy on us through the magnifying glass of machine learning.

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Dipayan Ghosh
The Automated Administrative State

The trend toward more prevalent and less transparent automation in agency decision-making is deeply concerning. The history and present of the administrative state’s addiction to automation suggest a need to make fresh choices regarding the future.

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Dipayan Ghosh
From Overconfidence in Research to Over Certainty in Policy Analysis: Can We Escape the Cycle of Hype and Disappointment?

Where researchers study the effects of social interventions and focus on statistically significant comparisons, their published results will, on average, overestimate effect sizes. And this happens even with honest, experienced, well-intentioned researchers using clean, randomized designs, as long as they are following standard practice and reporting statistically significant results.

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Dipayan Ghosh
The Moral Gray Space of AI Decisions

Artificial intelligence in diverse applications—from sex bots to war machines—is giving rise to equally diverse concerns: algorithmic bias, transparency, accountability, privacy, psychological impact, trust, and beyond. Of course, all of these issues don’t necessarily arise in all forms of AI; for instance, few people, if any, care about privacy with military robots. But one root ethical issue that does apply to the entire technology category is the general ability to make decisions. This is the linchpin issue to be examined here.

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Dipayan Ghosh
Follow the Data! Algorithmic Transparency Starts with Data Transparency

The data revolution that is transforming every sector of science and industry has been slow to reach the local and municipal governments and NGOs that deliver vital human services. The public sector is bound by a mandate for responsibility and transparency to the individuals and organizations it affects. What does this kind of data transparency look like, and how can it be built into the systems we design?

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Dipayan Ghosh
AI Marketing as a Trojan Horse

Computer-driven scoring and categorization engineer practical and prejudicial discriminations that separate those who don’t count from those who do, and decide the prices specific individuals receive compared to others.

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Dipayan Ghosh
Don’t Believe Every AI You See

The datasets and models used in these systems are not objective representations of reality. They are the culmination of particular tools, people, and power structures that foreground one way of seeing or judging over another.

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Dipayan Ghosh