Develops understanding of theories, management processes, organizational capabilities and social implications of criminal justice technologies. Many categories of technology are considered, ranging from communications and records management, to special assault and protection tactics. Students consider the role of industry, government, and user groups in the historical development and legal/ethical use of specific technologies.

Focuses on contemporary issues and topics not otherwise distinctly incorporated in established criminal justice courses. Concentrates on student discussion and interaction surrounding required readings on topics such as crime prevention and issues in the prosecution/court system. Recent examples include cyberlaw, prisoner re-entry restorative justice, wrongful convictions, crime mapping, crime analysis, non-traditional courts, legal controversies in the law, substance abuse, and legal research.

Artificial intelligence (AI) presents many complex issues for society, as technological developments have greatly outpaced public policy. Moreover, the open and commercialized nature of AI tools provides criminals and other adversarial actors with new advantages yet to be effectively countered. This class looks at the legal and policy frameworks and practices needed to build an ecosystem of privacy, security, and trust that will help ensure stakeholders that AI is being developed and deployed in an ethical, safe, and reliable manner. The class will also discuss how organizations are designing their own practices for operationalizing trustworthy or ethical AI in various sectors including law enforcement and criminal justice, commercial sectors, medical and biological research, among others. Students will be given a foundation in the emerging laws, regulations, and policies regarding AI, as well as insight on the broader process of how laws and policies need to adapt for other rapidly emerging technologies. We will explore in detail several approaches currently being considered, including regulatory approaches, standards, and considerations for national and international security. The course also will explore certain other legal issues arising in connection with AI, such antitrust and competition law, intellectual property and proprietary rights matters, and concerns for future technologies (quantum computing, AI and synthetic biology, etc.).

Artificial intelligence (AI) presents many complex issues for society, as technological developments have greatly outpaced public policy. Moreover, the open and commercialized nature of AI tools provides criminals and other adversarial actors with new advantages yet to be effectively countered. This class looks at the legal and policy frameworks and practices needed to build an ecosystem of privacy, security, and trust that will help ensure stakeholders that AI is being developed and deployed in an ethical, safe, and reliable manner. The class will also discuss how organizations are designing their own practices for operationalizing trustworthy or ethical AI in various sectors including law enforcement and criminal justice, commercial sectors, medical and biological research, among others. Students will be given a foundation in the emerging laws, regulations, and policies regarding AI, as well as insight on the broader process of how laws and policies need to adapt for other rapidly emerging technologies. We will explore in detail several approaches currently being considered, including regulatory approaches, standards, and considerations for national and international security. The course also will explore certain other legal issues arising in connection with AI, such antitrust and competition law, intellectual property and proprietary rights matters, and concerns for future technologies (quantum computing, AI and synthetic biology, etc.).

Special topics seminars offer an in-depth examination of current events, issues and problems unique to finance. Specific topics will vary depending upon student and faculty interests and on recent events in the business world. Seminar topics for a specific semester will be announced prior to the course offering. These seminars may be repeated for credit since topics will normally vary from semester to semester. (Instructor determined)

Special topics seminars offer an in-depth examination of current events, issues and problems unique to finance. Specific topics will vary depending upon student and faculty interests and on recent events in the business world. Seminar topics for a specific semester will be announced prior to the course offering. These seminars may be repeated for credit since topics will normally vary from semester to semester. (instructor-determined)

Vertically Integrated Projects (VIP) engage undergraduate students in long-term, large-scale, multidisciplinary project teams that are led by faculty. VIP courses are project-based, team-based courses directly supporting faculty research and scholarship. VIPs under this course number have a particular focus on interdisciplinary humanities and social sciences expertise, with membership in teams across RIT colleges.

Vertically Integrated Projects (VIP) engage undergraduate students in long-term, large-scale, multidisciplinary project teams that are led by faculty. VIP courses are project-based, team-based courses directly supporting faculty research and scholarship. VIPs under this course number have a particular focus on interdisciplinary humanities and social sciences expertise, with membership in teams across RIT colleges.

Vertically Integrated Projects (VIP) engage undergraduate students in long-term, large-scale, multidisciplinary project teams that are led by faculty. VIP courses are project-based, team-based courses directly supporting faculty research and scholarship. VIPs under this course number have a particular focus on interdisciplinary humanities and social sciences expertise, with membership in teams across RIT colleges.

Artificial intelligence (AI) presents many complex issues for society, as technological developments have greatly outpaced public policy. Moreover, the open and commercialized nature of AI tools provides criminals and other adversarial actors with new advantages yet to be effectively countered. This class looks at the legal and policy frameworks and practices needed to build an ecosystem of privacy, security, and trust that will help ensure stakeholders that AI is being developed and deployed in an ethical, safe, and reliable manner. The class will also discuss how organizations are designing their own practices for operationalizing trustworthy or ethical AI in various sectors including law enforcement and criminal justice, commercial sectors, medical and biological research, among others. Students will be given a foundation in the emerging laws, regulations, and policies regarding AI, as well as insight on the broader process of how laws and policies need to adapt for other rapidly emerging technologies. We will explore in detail several approaches currently being considered, including regulatory approaches, standards, and considerations for national and international security. The course also will explore certain other legal issues arising in connection with AI, such antitrust and competition law, intellectual property and proprietary rights matters, and concerns for future technologies (quantum computing, AI and synthetic biology, etc.).

Allows examination of a special problem or topical area in the field of public policy. Topics and specific content and methods vary from year to year or term to term.

Artificial intelligence (AI) presents many complex issues for society, as technological developments have greatly outpaced public policy. Moreover, the open and commercialized nature of AI tools provides criminals and other adversarial actors with new advantages yet to be effectively countered. This class looks at the legal and policy frameworks and practices needed to build an ecosystem of privacy, security, and trust that will help ensure stakeholders that AI is being developed and deployed in an ethical, safe, and reliable manner. The class will also discuss how organizations are designing their own practices for operationalizing trustworthy or ethical AI in various sectors including law enforcement and criminal justice, commercial sectors, medical and biological research, among others. Students will be given a foundation in the emerging laws, regulations, and policies regarding AI, as well as insight on the broader process of how laws and policies need to adapt for other rapidly emerging technologies. We will explore in detail several approaches currently being considered, including regulatory approaches, standards, and considerations for national and international security. The course also will explore certain other legal issues arising in connection with AI, such antitrust and competition law, intellectual property and proprietary rights matters, and concerns for future technologies (quantum computing, AI and synthetic biology, etc.).

This course will cover the major theoretical and applied analytical methods and techniques in both quantitative and qualitative analysis. An emphasis will be placed on integrating empirical and normative concerns.

Gives the student first-hand experience in designing and performing research. Students are closely supervised by a faculty member, developing their pre-professional skills while learning how to do research first hand. Allows examination of a special problem or topical area in the field of public policy at the graduate level. Topics and specific content and methods vary from year to year or semester to semester.