Machine vision. Data wrangling. Reinforcement learning. What do these terms even mean? In AI 101, MIT researcher Brandon Leshchinskiy offers an introduction to artificial intelligence that’s designed specifically for those with little to no background in the subject. The workshop starts with a summary of key concepts in AI, followed by an interactive exercise where participants train their own algorithm. Finally, it closes with a summary of key takeaways and Q/A. All are welcome!

The Student Guide to Artificial Intelligence is an initiative of Elon University, in partnership with the American Association of Colleges and Universities (AAC&U). It is a continuation of a 2023 global collaboration that established a statement of principles to guide development of AI policies and practices in higher education. The statement was released at the United Nations Internet Governance Forum in Kyoto, Japan, and was supported by more than 140 higher education organizations, administrators, researchers and faculty members from 48 countries.

NOTE -- Generative AI was used in the creation of this resources. You can find more information, including the prompts used, here: https://studentguidetoai.org/about/

This course instructs students on how to develop technologies that help people measure and communicate emotion, that respectfully read and that intelligently respond to emotion, and have internal mechanisms inspired by the useful roles emotions play.

This course explores a range of contemporary scholarship oriented to the study of ‘cybercultures,’ with a focus on research inspired by ethnographic and more broadly anthropological perspectives. Taking anthropology as a resource for cultural critique, the course will be organized through a set of readings chosen to illustrate central topics concerning the cultural and material practices that comprise digital technologies. We’ll examine social histories of automata and automation; the trope of the ‘cyber’ and its origins in the emergence of cybernetics during the last century; cybergeographies and politics; robots, agents and humanlike machines; bioinformatics and artificial life; online sociality and the cyborg imaginary; ubiquitous and mobile computing; ethnographies of research and development; and geeks, gamers and hacktivists. We’ll close by considering the implications for all of these topics of emerging reconceptualizations of sociomaterial relations, informed by feminist science and technology studies.

This course is conducted as an artificial intelligence programming contest in Java. Students work in teams to program virtual robots to play Battlecode, a real-time strategy game. Optional lectures are provided on topics and programming practices relevant to the game, and students learn and improve their programming skills experientially. The competition culminates in a live Battlecode tournament.
This course is offered during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Utopia or dystopia? It’s up to us.
In the 21st century, powerful technologies have been appearing at a breathtaking pace—related to the internet, artificial intelligence, genetic engineering, and more. They have amazing potential upsides, but we can’t ignore the serious risks that come with them.
Brave New Planet is a podcast that delves deep into the most exciting and challenging scientific frontiers, helping us understand them and grapple with their implications. Dr. Eric Lander, president and founding director of the Broad Institute of MIT and Harvard, is a geneticist, molecular biologist, and mathematician who was a leader of the Human Genome Project and for eight years served as a science advisor to the White House for President Obama. He’s also the host of Brave New Planet, and he’s talked to leading researchers, journalists, doctors, policy makers, activists, and legal experts to illuminate how this generation’s choices will shape the future as never before.
Brave New Planet is a partnership between the Broad Institute, Pushkin Industries, and the Boston Globe.

This is a class about applying autonomy to real-world systems. The overarching theme uniting the many different topics in this course will center around programming a cognitive robotic. This class takes the approach of introducing new reasoning techniques and ideas incrementally. We start with the current paradigm of programming you’re likely familiar with, and evolve it over the semester—continually adding in new features and reasoning capabilities—ending with a robust, intelligent system. These techniques and topics will include algorithms for allowing a robot to: Monitor itself for potential problems (both observable and hidden), scheduling tasks in time, coming up with novel plans to achieve desired goals over time, dealing with the continuous world, collaborating with other (autonomous) agents, dealing with risk, and more.

This course will explore the state of the art in common sense knowledge, and class projects will design and build interfaces that can exploit this knowledge to make more usable and helpful interfaces.
This year’s theme will be about how common sense knowledge differs in different languages and cultures, and how machine understanding of this knowledge can help increase communication between people, and between people and machines.

This course will explore the state of the art in common sense knowledge, and class projects will design and build interfaces that can exploit this knowledge to make more usable and helpful interfaces.
Course requirements will consist of critiques of class readings (about 2 papers/week), and a final project (paper or computer implementation project). Grades will be based primarily on the projects, as well as a small component for class and online participation

This course is an introduction to computational theories of human cognition. Drawing on formal models from classic and contemporary artificial intelligence, students will explore fundamental issues in human knowledge representation, inductive learning and reasoning. What are the forms that our knowledge of the world takes? What are the inductive principles that allow us to acquire new knowledge from the interaction of prior knowledge with observed data? What kinds of data must be available to human learners, and what kinds of innate knowledge (if any) must they have?

This course examines computers anthropologically, as artifacts revealing the social orders and cultural practices that create them. Students read classic texts in computer science along with cultural analyses of computing history and contemporary configurations. It explores the history of automata, automation and capitalist manufacturing; cybernetics and WWII operations research; artificial intelligence and gendered subjectivity; robots, cyborgs, and artificial life; creation and commoditization of the personal computer; the growth of the Internet as a military, academic, and commercial project; hackers and gamers; technobodies and virtual sociality. Emphasis is placed on how ideas about gender and other social differences shape labor practices, models of cognition, hacking culture, and social media.

This class addresses important, current debates in media with in-depth discussion of popular perceptions and policy implications. Students will engage in the critical study of the economic, political, social, and cultural significance of media, and learn to identify, analyze, and understand the complex relations among media texts, policies, institutions, industries, and infrastructures. This class offers the opportunity to discuss, in stimulating and challenging ways, topics such as ideology, propaganda, net neutrality, big data, digital hacktivism, digital rebellion, media violence, gamification, collective intelligence, participatory culture, intellectual property, artificial intelligence, etc., from historical, transcultural, and multiple methodological perspectives.

This subject offers a broad survey of texts (both literary and philosophical) drawn from the Western tradition and selected to trace the immediate intellectual antecedents and some of the implications of the ideas animating Darwin’s revolutionary On the Origin of Species. Darwin’s text, of course, is about the mechanism that drives the evolution of life on this planet, but the fundamental ideas of the text have implications that range well beyond the scope of natural history, and the assumptions behind Darwin’s arguments challenge ideas that go much further back than the set of ideas that Darwin set himself explicitly to question - ideas of decisive importance when we think about ourselves, the nature of the material universe, the planet that we live upon, and our place in its scheme of life. In establishing his theory of natural selection, Darwin set himself, rather self-consciously, to challenge a whole way of thinking about these things. The main focus of attention will be Darwin’s contribution to the so-called “argument from design” - the notion that innumerable aspects of the world (and most particularly the organisms within it) display features directly analogous to objects of human design and, since design implies a designer, that an intelligent, conscious agency must have been responsible for their organization and creation. Previously, it had been argued that such features must have only one of two ultimate sources - chance or conscious agency. Darwin proposed and elaborated a third source, which he called Natural Selection, an unconscious agency capable of outdoing the most complex feats of human intelligence.
The course of study will not only examine the immediate inspiration for this idea in the work of Adam Smith and Thomas Malthus and place Darwin’s Origin and the theory of Natural Selection in the history of ensuing debate, but it will also touch upon related issues.

Humans are social animals; social demands, both cooperative and competitive, structure our development, our brain and our mind. This course covers social development, social behaviour, social cognition and social neuroscience, in both human and non-human social animals. Topics include altruism, empathy, communication, theory of mind, aggression, power, groups, mating, and morality. Methods include evolutionary biology, neuroscience, cognitive science, social psychology and anthropology.

This is a video description of a study on artificial intelligence and ethics. The study is part of the requirements of the Development Communication 263 Course from the University of the Philippines Open University.

This is a short collection, which features the work of students in Dr. Mark Kinney's course, ICST 471, ANTH 470, SOCI 493: Enculturation and Spiritual  Development Across Cultures, taught at Evangel University, 2022-2023. The course has used the open textbook Discovering Cultural Anthropology by Antonia M. Santangelo. 

Artificial Intelligence (AI), and the algorithmic judgment at its core, is developing at breakneck speed. This version of the popular Ethics for Engineers course focuses on the ethics issues involved in the latest developments of computer science.

In an effort to build the capacity of the students and faculty on the topics of bias and fairness in machine learning (ML) and appropriate use of ML, the MIT CITE team developed capacity-building activities and material. This material covers content through four modules that an be integrated into existing courses over a one to two week period.

This course about financial technology, or FinTech, is for students wishing to explore the ways in which new technologies are disrupting the financial services industry—driving material change in business models, products, applications and customer user interface. Amongst the significant technological trends affecting financial services into the 2020’s, the class will explore AI, deep learning, blockchain technology and open APIs. Students will gain an understanding of the key technologies, market structure, participants, regulation and the dynamics of change being brought about by FinTech.

Advances in cognitive science have resolved, clarified, and sometimes complicated some of the great questions of Western philosophy: what is the structure of the world and how do we come to know it; does everyone represent the world the same way; what is the best way for us to act in the world. Specific topics include color, objects, number, categories, similarity, inductive inference, space, time, causality, reasoning, decision-making, morality and consciousness. Readings and discussion include a brief philosophical history of each topic and focus on advances in cognitive and developmental psychology, computation, neuroscience, and related fields. At least one subject in cognitive science, psychology, philosophy, linguistics, or artificial intelligence is required. An additional project is required for graduate credit.