HANNA KIRI GUNN

Unlike most philosophers who are housed in philosophy departments, I'm a faculty member of the graduate group in Cognitive and Information Sciences. This is an interdisciplinary department that includes a wide range of experts, methods, and approaches from a variety of cognitive science related disciplines, e.g., philosophy, computer science, neuroscience, linguistics, psychology. Please visit this page for further details on the interdisciplinary nature of our PhD and MA programs: https://cogsci.ucmerced.edu/graduate-program

Students who are interested in possibly working with me will likely be interested in working on interdisciplinary projects about choice and decision making; the manipulation, coercion, or persuasion of actions and beliefs; belief formation and belief maintenance; the ethical development of artificial intelligence (with a focus on expert learning systems, big data); or broadly themes within social, applied, and political epistemology. (See below for more details).

Potential graduate students who are considering working with me should understand that I am a trained philosopher within a CIS graduate program. I would strongly recommend any potential graduate students look at the work of my colleagues in the CIS program for another co-equal advisor who does experimental work in cognitive science. (Link to our faculty page: https://cogsci.ucmerced.edu/faculty). While I have my own background training in cognitive science, it is heavily theoretical and not experimental. Please email me if you have questions about this!

The following list of topics provides a sense of the kind of work that I do that connects with projects in cognitive science. I've written these lists as possible questions one might be interested in within the various areas:

• Choice and decision making (Broadly about actions)

  • What does it take for someone to make a free, informed choice? How might personalisation algorithms be supporting or undermining our ability to make these kinds of choices?

  • In what ways are we giving up human choice and decision making, and replacing it with algorithmic alternatives? Is this rational? Is this ethically defensible?

• Changing other's minds (Broadly about beliefs and desires , i.e., our cognitive attitudes)

  • We can't help but change other people's minds, but there are surely limits on when this is acceptable.

    • What's the difference between rationally persuading someone to believe something, and manipulating or coercing them to believe it?

    • Can manipulation or coercion produce justified belief?

    • Is it always wrong to manipulate or coerce someone into believing something?

  • What is gaslighting, and how might we explain the moral and epistemic badness of gaslighting others?

• Belief formation and belief maintenance

  • What should we believe, and why? How is social media changing the epistemic landscape that we occupy?

  • Why do viral beliefs seem to be more memorable?

  • What are echo chambers and filter bubbles? How might algorithms be causing these? How might our choices be causing these?

  • What is belief polarisation and what are its causes? What is political polarisation and what are its causes?

  • We take some personality traits or dispositions to be especially valuable for belief formation and belief maintenance, intellectual humility and open-mindedness are two. So,

    • What is intellectual humility? How does the intellectually humble person act? What might make people more or less intellectually humble? All of these same questions we can ask about open-mindedness.

    • What is it to be intellectually arrogant, dogmatic, or close-minded? How do these people act? What might make people more or less intellectually vicious in these ways?

• The ethical development of artificial intelligence

  • The status quo in the design, development, and deployment of artificial intelligence systems places low priority on ethical questions. What tools can be developed to support holistic, informed, and responsible development of these tools?

  • In what ways do pre-existing social and cultural biases manifest in and emerge from AI?

  • What kinds of policies and procedures can safeguard data sharing practices, especially across private and public sectors?

    • How should we understand rights to privacy in big data research?

    • What alternatives to informed consent processes are there for online applications?