• Weekly assignments – 15%
• Weekly Quiz – 15%
• Midterm Exam – 20%
• Final Presentation (group) – 20%
• Attendance & Participation – 10%
• Final Exam – 20%

Weeks 1 & 2 (XXXXXXX): Welcome to the course and Overview of AI

Definitions, history and applications of AI

• • Definitions
    • What is AI? What is Intelligence?
    • Types of AI: Narrow (weak) vs. General (strong) AI
  • History
    • Mythical beings, automata, and mechanical intelligence
    • Birth of AI – Turing, McCarthy, Minsky, Newell, etc.
    • AI Winters and Springs
    • Recent Developments – Deep Blue, Watson, AlphaGo, Deep Learning and
    • Generative AI
  • Applications
    • Personal assistants (Siri, Alexa)
    • Recommendation systems (Netflix, Amazon), and autonomous vehicles.
    • Business and Industry: Automated operations, predictive analytics, customer
    • service bots, and personalized marketing.
    • Healthcare: Diagnostics, personalized medicine, robotic surgery, patient data
    • management
    • Finance: Fraud detection, algorithmic trading, and personalized banking services.

Weeks  3 & 4   (XXXXX) Key concepts of AI

• Learning
  • Machine Learning
  • Deep Learning
• Logical Reasoning
  • Inductive
  • Deductive
• Natural Language Processing
  • translation
  • sentiment analysis
  • topic detection
• Problem Solving
  • Understanding
  • Representation
  • Feedback
  • Planning
• Perception
  • Vision
  • Speech
  • Gesture

Week 5 (XXXXXX): Fundamentals of Ethical Thinking

Normative ethics and common ethical theories.

• Overview of Consequentialism– Ethical outcomes. Maximize benefit/Minimize harm.   Egoism, Utilitarianism, Altruism.
• Overview of Deontology – Rights and Duties. Inherent/objective "rightness" or "wrongness" of actions. Kant's Categorical Imperative – treat others equally and with respect. Right to know, right to privacy, right to property. Treat others as you wish to be treated.
• Introduction to Ethics of Care -  Stresses the importance of caring for others and maintaining meaningful relationships as central to ethical considerations.
• Cyber/Informatics Ethics  -  How does informatics impact the concepts of ethics? Scope/Speed/Scale.  Anonymity and Identity. Technological Complexity.

Week 6 (XXXXXX): Fundamental concepts of Law

• Importance of Law – Protection of rights and freedoms. Social order. Dispute resolution. Governance and accountability. Regulation and public safety. Mechanism for social change and progress.
• Rule of Law – Everyone is subject to the law. It should be applied equally to individuals and those in authority.  Supremacy of law (ultimate authority). Should be applied equally and impartially.
• Legal Systems – Common Law - derived from judicial decisions and customs, rather than legislative statutes. Civil Law - relies less on precedent and more on explicit laws and regulations.
• Sources of Law - Constitutional law ensures the protection of individual rights and liberties, such as freedom of speech, religion, and privacy. Statutory law covers a wide range of legal issues and apply to specific jurisdictions.
• Branches of Law  -  Criminal vs. Civil law.

Week 7 (XXXXX): Review and Midterm Examination

Week 8 (XXXXXX): Fundamental concepts of Social Issues

• What are social issues?
• Common Social Issues – Social issues are often related to race, socio-economic class, and gender.  Some examples include, discrimination, poverty, access to resources and inequality.
• Properties of Social Issues – They often involve matters of inequality, justice, human rights, discrimination, and access to resources and opportunities.
• Impact on Individuals - Social exclusion, marginalization, disadvantage, and unequal distribution of resources and opportunities.
• Interconnectedness - Social issues are often interconnected. Addressing one issue may have ripple effects on other related issues. For example, poverty can be linked to education disparities, healthcare access, and crime rates.
• Role of Government and Institutions - Governments, institutions, and organizations have a responsibility to address social issues through policy development, implementation, and resource allocation.

Weeks 9 & 10 & 11 (XXXXX): Social, Legal, Ethical issues of Artificial Intelligence

• Privacy - The capability of AI to collect, analyze, and interpret vast amounts of personal data can lead to invasions of privacy and unauthorized use of personal information. How is gathered data used, shared, and potentially misused, includes issues of consent, transparency, and surveillance? Data breaches. Identity theft. How do we protect user data from unauthorized access, and complying with data breach notification laws?
• Bias and Discrimination - AI systems can perpetuate or even exacerbate biases present in their training data, leading to unfair outcomes. This is particularly concerning in critical applications like hiring, law enforcement, lending, and healthcare, where biased AI can affect people's lives significantly. AI may inadvertently amplify certain voices and perspectives while silencing others. Echo chambers, algorithmic bias, content moderation and platform governance.
• Transparency (explainability) - AI models, particularly deep learning algorithms, operate as "black boxes," where the decision-making process is opaque. This lack of transparency can make it difficult to understand how decisions are made, complicating efforts to evaluate fairness, accuracy, and accountability.
• Intellectual Property – Some AI applications can raise issues related to intellectual property, including copyright infringement, trademark violations, and plagiarism.
• Accountability - Accountability for decisions made by AI systems can be challenging. The complexity of AI systems can obscure the lines of responsibility, making it difficult to assign blame or liability for harmful decisions/actions/errors.
• Social Manipulation and Misinformation (Fake News) – AI-driven platforms can influence public opinion and behavior, raising concerns about social manipulation. The use of AI in spreading misinformation, shaping political discourse, and influencing elections poses significant ethical challenges. How does Artificial intelligence influence public opinion, and contribute to social polarization?
• Job Displacement - The automation of tasks previously performed by humans can lead to significant job displacement. While AI can create new job opportunities, there is concern over the potential for widespread unemployment or underemployment, especially in sectors highly susceptible to automation.
• Weaponization - Autonomous weapons systems powered by AI raise ethical concerns regarding the conduct of warfare. The prospect of machines making life-and-death decisions without human intervention presents profound moral and legal challenges.
• Commercialization and Manipulation – Topics such as targeted advertising, sponsored content, and influencer marketing. Such actions can impact transparency, authenticity, and manipulation of user behavior in the name of profits. This raises legal issues related to advertising regulations, disclosure requirements, and consumer protection laws.
• Cybersecurity and National Security - AI-driven cyberattacks present unique legal challenges, including attribution difficulties and the adequacy of existing cybercrime laws to address AI-specific threats. The use of AI in national defense raises legal issues regarding compliance with international humanitarian law and the laws of armed conflict.

Weeks 12 & 13 (XXXXXXX) : Operational Application of AI

• Students will experiment with high-level AI applications (e.g. Orange, RapidMiner, Deep Dream Generator, etc.)

Week 14 (XXXXXX): Future of Artificial Intelligence

• Transfer Learning:
• Energy-efficient AI

• AI and IoT (Internet of Things)
• AI and Blockchain3. Human-AI Collaboration

• Personalized Medicine and Predictive Healthcare

• Ethical AI

• Personalized Learning
• AI Tutors and Assistants

• Autonomous Earth and Space Exploration

• Creative AI
• AI information sensemaking
• AI as independent actors

Week 15 (XXXXXX): Work on group project/presentation

Week 16 (XXXXXX): Final Group Project/Presentation

Baase S, Henry T.. Gift of Fire : Social, Legal, and Ethical Issues for Computing Technology 5th Edition, Pearson; ISBN13: 978-0134615271,  2017.

Barfield W, Pagallo U. , Advanced Introduction to Law and Artificial Intelligence , Edward Elgar Publishing, ISBN13: 978-1789905144, 2020.

Broussard M., Artificial Unintelligence: How Computers Misunderstand the World , MIT Press, ISBN13: 978-0262038003, 2018.

Bostrom N., Yudkowsky E. , The Ethics of Artificial Intelligence, https://nickbostrom.com/ethics/artificial-intelligence.pdf, Cambridge Handbook of Artificial Intelligence, Cambridge University Press, 2011.

European Union, Artificial Intelligence Act, https://artificialintelligenceact.eu. 

Gebru T., Denton E., Addressing Bias in AI: Social Movements as a Model for Change, International Conference on Machine Learning, 2019.

Timnit G. et al., Fairness and Abstraction in Sociotechnical Systems, FAT* '19: Proceedings of the Conference on Fairness, Accountability, and Transparency, January 2019, Pages 59–68.

*Additional current articles/readings will be added.  Because the course will not be offered until F '25, those will be chosen closer to the offering date so that they are the most up-to-date readings available.

The new Applied Artificial Intelligence minor will benefit from a holistic, informatics-focused course that provides students from a variety of majors an opportunity to put into practice what they have learned in other Applied Artificial Intelligence minor courses.