Artificial Intelligence, Algorithms, and Society

DIGI61112 Artificial Intelligence, Algorithms, and Society 15 Semester 2 Postgraduate Taught Level 6 Sam Hind Unit coordinator 1 FHEQ level (Framework for Higher Education Qualifications) ' Masters/Integrated Masters P4 ' European Credit Transfer & Accumulation System Rating : 7.5 This unit will explore and examine the growing effect of artificial intelligence (AI) and algorithms on, and in, society. AI and algorithms are increasingly part of everyday life. From Midjourney to ChatGPT, AI is transforming the way people work, play, experience the world, and act within it. But what do AI and now dominant algorithmic methods such as machine learning (ML) involve, and what are the social, cultural, and political implications of their development and use? In this course unit we will explore what AI and algorithms do, and how artificial, algorithmic, and autonomous systems are being designed, developed, tested, funded, and built – with social, political, and cultural consequences. This unit will explore and examine the growing effect of artificial intelligence (AI) and algorithms on, and in, society. AI and algorithms are increasingly part of everyday life. From Midjourney to ChatGPT, AI is transforming the way people work, play, experience the world, and act within it. But what do AI and now dominant algorithmic methods such as machine learning (ML) involve, and what are the social, cultural, and political implications of their development and use? In this course unit we will explore what AI and algorithms do, and how artificial, algorithmic, and autonomous systems are being designed, developed, tested, funded, and built – with social, political, and cultural consequences. <ul> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">To introduce students to the role and effects of AI and algorithms in contemporary societies</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">To offer an overview of current debates around AI and algorithms in society</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">To provide a critical understanding of the possibilities, problems, and ethics of AI and algorithms</li></ul> <ul> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Critically evaluate the role of AI and algorithms in contemporary societies from a cultural, technical, and political perspective</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Examine how AI and algorithms are employed within contemporary societies, and how their use has different practical and ethical consequences</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Interpret and analyse how AI and algorithms are developed, designed, and operated</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Develop oral and written forms of interpretation and argumentation through a critical engagement with textual material, hands-on examination of technical objects, seminar discussions, and essay writing  </li></ul> <ul> <li style="text-align: justify;">Apply analytical skills to examine and analyse the effects of AI and algorithms in society</li> <li>Demonstrate knowledge and understanding of critical debates on AI and algorithms within media studies and related fields</li> <li>Articulate and explain key concepts concerning the implications of AI and algorithms for contemporary work, leisure, politics, culture, and the economy</li> <li>Demonstrate an awareness of the methodological approaches to understanding AI and algorithms, from different technical, cultural, and political perspectives</li></ul> <ul> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Engage in oral and written debates on a broad range of AI and algorithmic topics</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Build argumentative frameworks for the analysis of AI and algorithms from cultural perspectives</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Use digital and non-digital research materials and resources</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Follow academic referencing standards and norms in academic writing assignments</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Perform independent research involving the careful selection of appropriate material, topic, and case studies</li></ul> <ul> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Present information, ideas, arguments, and methodologies in respect to relevant parties</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Active and constructive participation in group activities</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Understanding and assessment of different perspectives</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Demonstrate analytical abilities</li> <li style="margin-bottom: 11px; text-align: justify; margin-left: 8px;">Demonstrate critical evaluative skills in relation to AI, algorithms, and digital media</li></ul> Analytical skills Deploy critical evaluative skills to situations or settings where AI and algorithms might be used Innovation/creativity Respond and adapt to criticism levelled at applications of AI and algorithms Problem solving Understand how AI and algorithmic services might discriminate against and alienate certain users Other Develop an understanding of how AI and algorithms can be used in an applied context The course unit is divided into two (parallel) sections, corresponding to the lecture component and the seminar component. In Section I: Understanding AI students will consider what AI is (and isn’t), the history of automation, what machine learning involves, how big tech platforms dominate the world of AI, and what the ensuing environmental impacts of an AI-driven world are. In consecutive weeks, students will explore different aspects of AI in their situated, social contexts, from the practices of ‘ground-truthing’ to AI industrial policy. In Section II: Exploring AI students will have the opportunity to experiment with key aspects of the AI ‘pipeline’ through practical activities and workshops. Following a wide range of experimental, creative approaches, students will learn how data is prepared for AI purposes, how machine learning models are designed and tested, and how AI services and competitions are delivered and organized. In the second half of the course unit, students will complete a project designed to examine the growing social, cultural, and political pressures AI is exerting on the world. The unit consists of 1-hour lectures, 2-hour seminars, and 1-hour drop-in sessions. The lecture component will ordinarily consist of introductions to each AI topic, as well as key epistemological, ontological, political, cultural, and ethical debates around them. The seminar component will consist of (guided) practical workshops in which students will have the opportunity to creatively use, explore, and experiment with different AI tools, platforms, software, services, and platforms. The seminar component will also be used for students to develop their group projects, offering the opportunity for collaborative experimentation as well as the space for informal feedback and advice. All supporting material will be provided via a corresponding Blackboard course unit page. Drop-in sessions will allow students to hone assessment work if desired. 2 Written assignment (inc essay) 100% <table cellspacing="0" class="Table" style="border-collapse:collapse; border:none; margin-left:7px; width:643px"> <tbody> <tr> <td>Feedback method</td> <td>Formative and/or Summative</td> </tr> <tr> <td>Written (Blackboard, email)</td> <td>Formative</td> </tr> <tr> <td>Verbal (office hours, in-class)</td> <td>Formative and summative</td> </tr> <tr> <td>Turnitin</td> <td>Summative</td> </tr> </tbody></table> N Amaro, R. (2022) The Black Technical Object: On Machine Learning and the Aspiration of Black Being. Berlin: Sternberg Press.Amoore, L. (2020) Cloud Ethics: Algorithms and the Attributes of Ourselves and Others. Durham, NC: Duke University Press.Andrejevic, M. (2019) Automated Media. London: Routledge.Crawford, K. and Joler, V. (2018) Anatomy of an AI system. Anatomy of AI <a href="https://anatomyof.ai/">https://anatomyof.ai/</a>Golumbia, D. (2009) The Cultural Logic of Computation. Cambridge, MA: Harvard University Press.Hayles, K. (2017) Unthought: The Power of the Cognitive Nonconscious. Chicago, IL: The University of Chicago Press.Jaton, F. (2021a) The Constitution of Algorithms: Ground-Truthing, Programming, Formulating. Cambridge, MA: MIT Press.Mackenzie, A. (2017) Machine Learners: Archaeology of a Data Practice. Cambridge, MA: MIT Press.Roberge, J. and Castelle, M. (2020) (eds.) The Cultural Life of Machine Learning: An Incursion into Critical AI Studies. Cham: Palgrave Macmillan Lectures 6 Seminars 12 Tutorials 4 0 278