Milo Phillips-Brown
Biographic Data
| ID | 9013656 |
|---|---|
| NAME | Milo Phillips-Brown |
| GIVEN NAMES | Milo |
| FAMILY NAME | Phillips-Brown |
| SIGNATURE | PHILLIPS-BROWN M |
| AFFILIATIONS | University of Edinburgh |
| ORCID | 0000-0003-2223-9445 |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 0 |
| AUTHOR COUNT | 6 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2019 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 0 |
Algorithmic Neutrality
Algorithms wield increasing power over our lives. They can and often do wield that power unfairly, and much has been said about algorithmic fairness. In contrast, algorithmic neutrality has been largely neglected. I investigate algorithmic neutrality, asking: What is it? Is it possible? And what is its normative significance
Desiderative Lockeanism
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. I advance a new Desiderative Lockean view. My view is distinctive in being doubly context-sensitive. Want ascriptions exhibit a remarkable context-sensitivity: what a person is truly said to want varies by context in a variety of ways, a fact that has not been fully appreciated. O…
Some-things-considered desire
Conflicting desire ascriptions — ascriptions of the form ⌜S wants p⌝ and ⌜S wants ¬p⌝ — falsify every extant semantics that takes the orthodox, and theoretically powerful, belief-based approach to desire ascriptions. In many cases, these semantics wrongly predict that conflicting desire ascriptions can’t both be true. In response, I propose a semantics of some-things-considered, other-things-ignored desire, which I model with questions — lending …
(Counter)factual Want Ascriptions and Conditional Belief
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 …
We might be afraid of black-box algorithms
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. Durán and Jongsma (2021) have recently sought to allay such fears. While some of their arguments are compelling, we still see reasons for fear
Anankastic conditionals are still a mystery
‘If you want to go to Harlem, you have to take the A train’ doesn’t look special. Yet a compositional account of its meaning, and the meaning of anankastic conditionals more generally, has proven an enigma. Semanticists have responded by assigning anankastics a unique status, distinguishing them from ordinary indicative conditionals. Condoravdi & Lauer (2016) maintain instead that “anankastic conditionals are just conditionals.” I argue that Cond…
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Anankastic conditionals are still a mystery
‘If you want to go to Harlem, you have to take the A train’ doesn’t look special. Yet a compositional account of its meaning, and the meaning of anankastic conditionals more generally, has proven an enigma. Semanticists have responded by assigning anankastics a unique status, distinguishing them from ordinary indicative conditionals. Condoravdi & Lauer (2016) maintain instead that “anankastic conditionals are just conditionals.” I argue that Cond…
We might be afraid of black-box algorithms
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. Durán and Jongsma (2021) have recently sought to allay such fears. While some of their arguments are compelling, we still see reasons for fear
(Counter)factual Want Ascriptions and Conditional Belief
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 …
Desiderative Lockeanism
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. I advance a new Desiderative Lockean view. My view is distinctive in being doubly context-sensitive. Want ascriptions exhibit a remarkable context-sensitivity: what a person is truly said to want varies by context in a variety of ways, a fact that has not been fully appreciated. O…
Some-things-considered desire
Conflicting desire ascriptions — ascriptions of the form ⌜S wants p⌝ and ⌜S wants ¬p⌝ — falsify every extant semantics that takes the orthodox, and theoretically powerful, belief-based approach to desire ascriptions. In many cases, these semantics wrongly predict that conflicting desire ascriptions can’t both be true. In response, I propose a semantics of some-things-considered, other-things-ignored desire, which I model with questions — lending …
Algorithmic Neutrality
Algorithms wield increasing power over our lives. They can and often do wield that power unfairly, and much has been said about algorithmic fairness. In contrast, algorithmic neutrality has been largely neglected. I investigate algorithmic neutrality, asking: What is it? Is it possible? And what is its normative significance
Computer Science (4 works) · Epistemology, Ethics, and Metaphysics (4 works) · Philosophy (3 works) · Epistemology (2 works) · Ethics and Social Impacts of AI (2 works) · Mathematics (2 works) · Philosophy and Theoretical Science (2 works) · Artificial Intelligence (1 works) · Artificial Intelligence in Healthcare and Education (1 works) · Black box (1 works)