self-regulation

Dark Patterns Powered by Machine Learning: The Role of Behavioral Science Ethics

Dark patterns, the “sludges” of the digital world, aim to distort consumers’ decision-making process. Dark patterns powered by machine learning represent an even higher threat, in that they don’t just trick users to do something, but alter human behavior in a durable, undetectable, and indefensible way. This article examines the main issues linked to machine learning powered dark patterns and seeks to outline possible solutions.

Exerting Self-Control ≠ Sacrificing Pleasure

In the typical self-control experiment, participants are given a choice between a hedonic vice-food (e.g., chocolate) and a utilitarian virtue-food (e.g., fruit). Choosing the hedonic vice is interpreted as a self-control failure. We argue that self-control failures are better captured as choices that violate one’s long-term goals and induce regret. Accordingly, the consumption of hedonic food is not necessarily a self-control failure, and self-control does not necessarily entail a trade-off between pleasure and health. Our conceptualization has far-reaching consequences for consumers and policy-makers who try to help consumers exert self-control.

Why Financial Education Needs a Primer in Behavioral Science

Many people are struggling financially. Figures from the Money Advice Service and DWP show that half of people say that they are worried about their finances, four in 10 people say that they could not easily cover an unexpected bill of £300, and 40% working age people in the UK face inadequate incomes in retirement. [...]

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