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