9 found
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  1. What does decision theory have to do with wanting?Milo Phillips-Brown - 2021 - Mind 130 (518):413-437.
    Decision theory and folk psychology both purport to represent the same phenomena: our belief-like and desire- and preference-like states. They also purport to do the same work with these representations: explain and predict our actions. But they do so with different sets of concepts. There's much at stake in whether one of these two sets of concepts can be accounted for with the other. Without such an account, we'd have two competing representations and systems of prediction and explanation, a dubious (...)
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  2. Desiderative Lockeanism.Milo Phillips-Brown - forthcoming - Australasian Journal of Philosophy.
    According to the Desiderative Lockean Thesis, there are necessary and sufficient conditions, stated in the terms of decision theory, for when one is truly said to want. What one is truly said to want, it turns out, varies remarkably by context—and to an underappreciated degree. To explain this context-sensitivity—and closure properties of wanting—I advance a Desiderative Lockean view that is distinctive in having two context-sensitive parameters.
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  3. (Counter)factual want ascriptions and conditional belief.Thomas Grano & Milo Phillips-Brown - 2022 - Journal of Philosophy 119 (12):641-672.
    What are the truth conditions of want ascriptions? According to an influential approach, they are intimately connected to the agent’s beliefs: ⌜S wants p⌝ is true iff, within S’s belief set, S prefers the p worlds to the not-p worlds. This approach faces a well-known problem, however: it makes the wrong predictions for what we call (counter)factual want ascriptions, wherein the agent either believes p or believes not-p—for example, ‘I want it to rain tomorrow and that is exactly what is (...)
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  4. I want to, but...Milo Phillips-Brown - 2018 - Sinn Und Bedeutung 21:951-968.
    You want to see the concert, but don’t want to take a long drive (even though the concert is far away). Such *strongly conflicting desire ascriptions* are, I show, wrongly predicted incompatible by standard semantics. I then object to possible solutions, and give my own, based on *some-things-considered desire*. Considering the fun of the concert, but ignoring the drive, you want to see the concert; considering the boredom of the drive, but ignoring the concert, you don’t want to take the (...)
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  5. We might be afraid of black-box algorithms.Carissa Veliz, Milo Phillips-Brown, Carina Prunkl & Ted Lechterman - 2021 - Journal of Medical Ethics 47.
    Fears of black-box algorithms are multiplying. Black-box algorithms are said to prevent accountability, make it harder to detect bias and so on. Some fears concern the epistemology of black-box algorithms in medicine and the ethical implications of that epistemology. In ‘Who is afraid of black box algorithms? On the epistemological and ethical basis of trust in medical AI,' Durán and Jongsma seek to allay such fears. While some of their arguments are compelling, we still see reasons for fear.
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  6. Algorithmic neutrality.Milo Phillips-Brown - manuscript
    Algorithms wield increasing control over our lives—over the jobs we get, the loans we're granted, the information we see online. Algorithms can and often do wield their power in a biased way, and much work has been devoted to algorithmic bias. In contrast, algorithmic neutrality has been largely neglected. I investigate algorithmic neutrality, tackling three questions: What is algorithmic neutrality? Is it possible? And when we have it in mind, what can we learn about algorithmic bias?
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  7. Getting what you want.Lyndal Grant & Milo Phillips-Brown - 2020 - Philosophical Studies 177 (7):1791-1810.
    The compelling, widely-accepted Satisfaction-is-Truth Principle says that if S wants p, then S has a desire that's satisfied in exactly the worlds where p is true. We reject the Principle; an agent may want p without having a desire that's satisfied when p obtains in any old way. Other theorists who reject the Principle rely on contested intuitions about when agents get what they want. We instead appeal to—and shed new light on—the dispositional role of desire.
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  8. Authenticity and co-design: On responsibly creating relational robots for children.Milo Phillips-Brown, Marion Boulicault, Jacqueline Kory-Westland, Stephanie Nguyen & Cynthia Breazeal - 2023 - In Mizuko Ito, Remy Cross, Karthik Dinakar & Candice Odgers (eds.), Algorithmic Rights and Protections for Children. MIT Press. pp. 85-121.
    Meet Tega. Blue, fluffy, and AI-enabled, Tega is a relational robot: a robot designed to form relationships with humans. Created to aid in early childhood education, Tega talks with children, plays educational games with them, solves puzzles, and helps in creative activities like making up stories and drawing. Children are drawn to Tega, describing him as a friend, and attributing thoughts and feelings to him ("he's kind," "if you just left him here and nobody came to play with him, he (...)
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  9. Anankastic conditionals are still a mystery.Milo Phillips-Brown - 2019 - Semantics and Pragmatics 12 (13):1-17.
    A compositional semantics for anankastic conditionals (‘If you want p, you must φ’) has been elusive. Condoravdi and Lauer (2016) decisively object to all semantics that precede their own. CL's view rests on a response to *the problem of conflicting goals*; CL use an interpretation of 'want' on which an agent's desires don't conflict with her beliefs. But a proper response requires lack of conflict with the facts. CL's view fails. Anankastic conditionals are still a mystery.
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