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61 - 70 of 76 results for: artificial intelligence

PHIL 253L: Computing Machines and Intelligence (PHIL 153L)

In this course we will explore the central question of what intelligence is by adopting artificial intelligence research as a point of reference. Starting with ideas proposed by Alan Turing in his 1950 paper, we will see what the contemporary interpretations are for those questions, and learn what new questions new technologies have brought. Among the subtopics are: Is it possible for a computer to think? What is thought? Are we computers? Could machines feel emotions or be conscious? Can AI die? Is there a relation between AI and decidability? What is the relationship between AI and Neuroscience Research? nThis course is intended for students of different majors interested in learning how the researchers in AI understand today the concept of intelligent machine, and examine what are the philosophical problems associated with the concept of artificial intelligence.
Terms: not given this year, last offered Autumn 2018 | Units: 4 | Grading: Letter or Credit/No Credit

PHIL 356C: Logic and Artificial Intelligence (CS 257)

This is a course at the intersection of philosophical logic and artificial intelligence. After reviewing recent work in AI that has leveraged ideas from logic, we will slow down and study in more detail various components of high-level intelligence and the tools that have been designed to capture those components. Specific areas will include: reasoning about belief and action, causality and counterfactuals, legal and normative reasoning, natural language inference, and Turing-complete logical formalisms including (probabilistic) logic programming and lambda calculus. Our main concern will be understanding the logical tools themselves, including their formal properties and how they relate to other tools such as probability and statistics. At the end, students should expect to have learned a lot more about logic, and also to have a sense for how logic has been and can be used in AI applications. Prerequisites: A background in logic, at least at the level of Phil 151, will be expected. In case a student is willing to put in the extra work to catch up, it may be possible to take the course with background equivalent to Phil 150 or CS 157. A background in AI, at the level of CS 221, would also be very helpful and will at times be expected. 2 unit option only for PhD students past the second year. Course website: http://web.stanford.edu/class/cs257/
Terms: not given this year, last offered Winter 2018 | Units: 2-4 | Grading: Letter or Credit/No Credit

POLISCI 134P: Contemporary Moral Problems (ETHICSOC 185M, PHIL 72)

This course is an introduction to contemporary ethical thought with a focus on the morality of harming others and saving others from harm. It aims to develop students' ability to think carefully and rationally about moral issues, to acquaint them with modern moral theory, and to encourage them to develop their own considered positions about important real-world issues. In the first part of the course, we will explore fundamental topics in the ethics of harm. Among other questions, we will ask: How extensive are one's moral duties to improve the lives of the less fortunate? When is it permissible to inflict harm on others for the sake of the greater good? Does the moral permissibility of a person's action depend on her intentions? Can a person be harmed by being brought into existence? In the second part of the course, we will turn to practical questions. Some of these will be familiar; for example: Is abortion morally permissible? What obligations do we have to protect the planet for the sake of future generations? Other questions we will ask are newer and less well-trodden. These will include: How does the availability of new technology, in particular artificial intelligence, change the moral landscape of the ethics of war? What moral principles should govern the programming and operation of autonomous vehicles?
Terms: Win | Units: 4-5 | UG Reqs: GER:EC-EthicReas, WAY-ER | Grading: Letter (ABCD/NP)

POLISCI 182: Ethics, Public Policy, and Technological Change (COMM 180, CS 182, ETHICSOC 182, PHIL 82, PUBLPOL 182)

Examination of recent developments in computing technology and platforms through the lenses of philosophy, public policy, social science, and engineering. Course is organized around four main units: algorithmic decision-making and bias; data privacy and civil liberties; artificial intelligence and autonomous systems; and the power of private computing platforms. Each unit considers the promise, perils, rights, and responsibilities at play in technological developments. Prerequisite: CS106A.
Terms: Win | Units: 5 | UG Reqs: WAY-ER | Grading: Letter or Credit/No Credit

PSYCH 147S: Introduction to the Psychology of Emotion

What are emotions? What purpose do they serve? How do we measure them? Can we control them? In this course, we will explore some of the most interesting questions in psychology: questions about emotion. Emotions shape our perceptions of the world, influence critical life decisions, and allow us to connect with others. This seminar will provide a selective review of the scientific study of emotion in Affective Science. The first unit of the course will focus on the theoretical foundations, the basic science of emotion, and methods for measuring emotions. In the second unit of the course, we will discuss topics at the intersection of motivation and emotion, such as decision-making and self-control. In the third unit, we will delve into the social function of emotions. In the fourth unit of the course, we will study the ways people succeed and fail at controlling their emotions. In the fifth unit, we will discuss a variety of additional topics such as how emotions change across the lifespan, how emotions can be harnessed to engineer behavior change, as well as emotions and artificial intelligence. My goal is that you will leave this course with a scientifically-informed understanding of your own and others' emotions as well as strategies for how to effectively use and manage your feelings in daily life.
Terms: Sum, last offered Summer 2019 | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 247: Topics in Natural and Artificial Intelligence

We will read a selection of recent papers from psychology, computer science, and other fields. We will aim to understand: How human-like are state of the art artificial intelligence systems? Where can AI be better informed by recent advances in cognitive science? Which ideas from modern AI inspire new approaches to human intelligence? Specific topics will be announced prior to the beginning of term.
Terms: not given this year, last offered Autumn 2018 | Units: 3 | Grading: Letter or Credit/No Credit

PSYCH 291: Causal Cognition

Causality is central to our understanding of the world and of each other. We think causally when we predict what will happen in the future, infer what happened in the past, and interpret other people's actions and emotions. Causality is intimately linked to explanation -- to answering questions about why something happened. In this discussion-based seminar class, we will first read foundational work in philosophy that introduces the main frameworks for thinking about causation. We will then read some work on formal and computational theories of causation that was inspired by these philosophical frameworks. Equipped with this background, we will study the psychology of causal learning, reasoning, and judgment. We will tackle questions such as: How can we learn about the causal structure of the world through observation and active intervention? What is the relationship between causal reasoning and mental simulation? Why do we select to talk about some causes over others when several causes led to an outcome? Toward the end of the course, we will discuss how what we have learned in psychology about causation may be useful for other fields of inquiry, such as legal science as well as machine learning and artificial intelligence.
Terms: not given this year, last offered Spring 2019 | Units: 3 | Grading: Letter or Credit/No Credit

PUBLPOL 182: Ethics, Public Policy, and Technological Change (COMM 180, CS 182, ETHICSOC 182, PHIL 82, POLISCI 182)

Examination of recent developments in computing technology and platforms through the lenses of philosophy, public policy, social science, and engineering. Course is organized around four main units: algorithmic decision-making and bias; data privacy and civil liberties; artificial intelligence and autonomous systems; and the power of private computing platforms. Each unit considers the promise, perils, rights, and responsibilities at play in technological developments. Prerequisite: CS106A.
Terms: Win | Units: 5 | UG Reqs: WAY-ER | Grading: Letter or Credit/No Credit

STATS 315B: Modern Applied Statistics: Data Mining

Two-part sequence. New techniques for predictive and descriptive learning using ideas that bridge gaps among statistics, computer science, and artificial intelligence. Emphasis is on statistical aspects of their application and integration with more standard statistical methodology. Predictive learning refers to estimating models from data with the goal of predicting future outcomes, in particular, regression and classification models. Descriptive learning is used to discover general patterns and relationships in data without a predictive goal, viewed from a statistical perspective as computer automated exploratory analysis of large complex data sets.
Terms: Spr | Units: 3 | Grading: Letter or Credit/No Credit
Instructors: Friedman, J. (PI)

SYMBSYS 2: Sym Sys: Many Parts, Cohesive Whole

The ten branches of the Symbolic Systems major: applied logic, artificial intelligence, cognitive science, computer music, decision making and rationality, human-computer interaction, learning, natural language, neurosciences, and philosophical foundations. Students unfamiliar with the major gain an overview of its branches; students recently involved with the major gain a better idea of which track they should pursue; and students already familiar with the major gain understanding of how the different branches of the program fit together. Sources include films, readings, and presentations by and discussions with Stanford professors and recent alumni.
Terms: not given this year, last offered Spring 2009 | Units: 1 | Grading: Satisfactory/No Credit
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