This course aims to provide students with a deep understanding of the ethical issues and potential risks associated with the design, development, and deployment of AI systems. It also explores strategies for mitigating these risks. The course covers accountability and risk assessment frameworks that help ensure ethical AI decision-making. Additionally, it examines the resource demands of training and deploying AI systems, emphasizing the need for sustainable solutions. Topics include societal concerns such as bias, data privacy, human autonomy, and copyright violations, as well as technical issues like explainability, vulnerabilities to attacks, technical robustness, and sustainability. The course will also review key design frameworks and toolkits that can help evaluate and mitigate ethical AI risks.
| Academic Units | 3 |
| Exam Schedule | Not Applicable |
| Grade Type | Letter Graded |
| Department Maintaining | CSC(CE) |
| Not Available to Programme | ACBS, ACC, ACDA, ADM, AERO, ARED, ASEC, BACF, BASA, BCE, BCG, BEEC, BIE, BMS, BS, BSB, BSPY, BUS, CBE, CBEC, CE, CEE, CEEC, CHEM, CHIN, CMED, CNEL, CNLM, COMP, CS, CSC, CSEC, CVEC, DSAI, ECDS, ECMA, ECON, ECPP, ECPS, EEE, EEEC, EESS, ELAH, ELH, ELHS, ELPL, ENE, ENEC, ENG, ESPP, HIST, HSCN, HSLM, IEEC, IEM, LMEL, LMPL, LMS, MACS, MAEC, MAEO, MAT, MATH, ME(DES), ME(IMS), ME(NULL), ME(RMS), MEEC(DES), MEEC(IMS), MEEC(NULL), MEEC(RMS), MS, MS-2ndMaj/Spec(MSB), MTEC, PESC, PHIL, PHMS, PHY, PLCN, PLHS, PPGA, PSLM, PSMA, PSY, REP, ROBO, SCED, SOC, SPPE, SSM |
| Index | Type | Group | Day | Time | Venue | Remark |
|---|
0930
1030
1130
1230
1330
1430
1530
1630
1730
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