Temporary Microcredential Online Course Instructor- AI Literacy and Policy Fundamentals Understanding and Mitigating Algorithmic Bias

Temporary Microcredential Online Course Instructor: AI Literacy and Policy Fundamentals: Understanding and Mitigating Algorithmic Bias

Location: Remote (U.S. based only)
Division: Rabb School of Continuing Studies in collaboration with the Heller School of Social Policy and Management Brandeis University
Compensation: $2000

Estimated Time Commitment: Approximately 30 -35 hours (4 hours per week) over the eight week course period including weekly synchronized sessions preparation learner support assignment review and coordination with program team.

Brandeis Universitys Rabb School of Continuing Studies working in collaboration with the Heller School for Social Policy and Management is seeking an experienced Instructor to teach a non-credit-bearing microcredential course titled AI Literacy and Policy Fundamentals: Understanding and Mitigating Algorithmic Bias.

This course will be delivered in a hybrid online modality combining a weekly synchronous instruction with asynchronous learning activities. The instructor will facilitate live online sessions guide learners through course materials review assignments respond to learner questions and support an engaging and accessible learning experience.

The course introduces learners to foundational concepts in artificial intelligence algorithmic bias responsible AI and policy approaches to mitigating harm. It examines how AI systems can reproduce or amplify inequities how bias affects decision-making processes and what ethical technical and policy strategies can be used to build fairer and more accountable AI systems.

The ideal candidate will bring strong subject-matter expertise experience teaching adult or graduate-level learners and the ability to translate complex interdisciplinary content into clear practical and engaging instruction.

The Instructor will be responsible for teaching and facilitating the course in accordance with Brandeis academic expectations and course design standards.

Responsibilities include:

• Facilitate one 90-minute synchronous online session each week.

• Prepare for weekly sessions by reviewing course materials assignments learner progress and discussion topics.

• Deliver clear engaging instruction on AI literacy algorithmic bias responsible AI AI ethics and policy fundamentals.

• Support learners in connecting course concepts to real-world applications in public policy social impact workforce settings and organizational decision-making.

• Review and provide feedback on assignments reflections applied exercises or other course assessments.

• Respond to learner questions in a timely and professional manner.

• Monitor asynchronous learner engagement including discussion boards or LMS-based activities as applicable.

• Coordinate with Brandeis Online RJxTP and/or program staff regarding course delivery learner concerns scheduling and completion requirements.

• Uphold Brandeis Universitys academic standards accessibility expectations and online learning guidelines.

• Participate in brief onboarding or course planning meetings before the start of the course as needed.

• Provide light post-course input or feedback to support course improvement and future offerings.

• PhD masters degree or equivalent professional qualifications in artificial intelligence machine learning public policy data science ethics social policy technology policy or a related field.

• Demonstrated expertise in algorithmic bias responsible AI AI ethics public policy or technology governance.

• Minimum 2 years of relevant professional academic or applied experience.

• Prior teaching training facilitation or instructional experience with adult learners graduate students or professional audiences.

• Ability to explain complex technical and policy concepts in accessible and practical ways.

• Strong communication organization and learner-support skills.

• Comfort using LMS platforms video conferencing tools and online teaching technologies.

• Ability to work independently while coordinating with program and online learning teams.

• Experience teaching or facilitating online hybrid or asynchronous courses.

• Experience working across interdisciplinary fields such as AI public policy social justice health equity education workforce development or technology governance.

• Familiarity with applied case studies involving algorithmic bias in areas such as healthcare hiring education finance public benefits criminal justice or civic systems.

• Experience designing or supporting learner-centered assignments applied exercises simulations or policy analysis activities.

• Experience working with diverse learners professional audiences or community-engaged educational programs.

• Fully remote position.

• U.S.-based applicants only.

• No visa sponsorship available.

• Weekly live session commitment: 90 minutes per week.

• Additional expected time includes preparation assignment review learner communication LMS engagement and coordination with program staff.

• Estimated total commitment: approximately 3035 hours over the 8 week session.

• Compensation: $2000.

The Universitys pay ranges represent a good faith estimate of what Brandeis reasonably expects to pay for a position at the time of posting. The pay offered to a selected candidate during hiring will be based on factors such as (but not limited to) the scope and responsibilities of the position the candidates work experience and education/training internal peer equity and applicable legal requirements.

Brandeis University is an equal opportunity employer which does not discriminate against any applicant or employee on the basis of race color ancestry religious creed gender identity and expression national or ethnic origin sex sexual orientation pregnancy age genetic information disability caste military or veteran status or any other category protected by law (also known as membership in a protected class).