As organizations increasingly rely on artificial intelligence and automated decision-making tools, employers and their counsel face expanding exposure under federal, state, and local employment laws. This course examines the legal, ethical, and operational risks associated with algorithmic workplace management, including potential liability under Title VII, the Americans with Disabilities Act (ADA), and the Age Discrimination in Employment Act (ADEA), as well as emerging regulatory frameworks governing automated employment decision tools.
Drawing on real-world scenarios and current enforcement trends, this program explores how overreliance on predictive systems can lead to biased outcomes, diminished human oversight, and compliance failures — even when organizations believe they are acting objectively. We will consider “non-delegable duties” in the context of AI-assisted decision-making and review practical examples of liability arising from inadequate supervision of automated tools.
The course introduces a structured, human-centered approach to integrating technology into workplace systems. Using a Human-in-the-Loop (HITL) framework, attendees will learn how to define appropriate boundaries between automated processes and human judgment, implement internal safeguards to reduce legal exposure, and respond effectively to workplace conflicts amplified by algorithmic systems.
Participants will leave with practical tools and risk-mitigation strategies to help them:
- Identify potential discrimination risks in hiring, evaluation, and discipline systems
- Align AI use with existing legal obligations and emerging guidance
- Strengthen organizational accountability and documentation practices
- Preserve professional judgment and ethical responsibility in technology-assisted environments
This course is designed for attorneys, compliance professionals, and organizational leaders seeking to responsibly integrate AI into workplace practices while maintaining legal compliance and sustainable, human-centered operations.
- Overview
- The Squeeze of the Modern Work Environment: An introduction to the modern version of the "entrepreneurial seizure" discussed in Michael E. Gerber’s The E-Myth Revisited and the competing pressures facing today’s leaders.
- The Mechanics of Triangulation: Mapping the tensions among executive autonomy, regulatory compliance obligations, and workforce exhaustion.
- The Technological Mirage: How over-reliance on automated decision-making systems can defer — rather than resolve — organizational risk.
- The Vulnerabilities of Algorithmic Management & Legal Floors
- The "Flawed Assistant" Reality: Generative AI has limitations that create risks (e.g., hallucinations, lack of contextual reasoning, absence of moral judgment).
- The Behavioral Loop and Cognitive Capture: As NBC News Technology Correspondence Jacob Ward discusses in The Loop, automation can reinforce “System-1” decision-making and diminish critical managerial oversight.
- Automated Gatekeeping and Class-Action Discrimination Vectors: Employers risk legal exposure when they purchase hiring and screening tools, since they might incorporate bias from flawed historical training data.
- Title VII of the Civil Rights Act of 1964 (42 U.S.C. § 2000e)
- Age Discrimination in Employment Act (29 U.S.C. § 621 et seq.)
- Americans with Disabilities Act (42 U.S.C. § 12101 et seq.)
- NYC Local Law 144 (Automated Employment Decision Tools): Requires bias audits and notice to candidates/employees
- The Non-Delegable Duty Doctrine: Why legal accountability remains with human professionals despite reliance on algorithmic tools.
- ABA Model Rule 5.1 & 5.3: Supervisory responsibility for non-lawyers (including tech vendors)
- ABA Model Rule 1.1 (Comment 8): Duty of technological competence
- Mata v. Avianca, Inc. (S.D.N.Y. 2023): AI hallucinations cited in court filings → sanctions risk
- The Migration of Strategic Value: The increasing importance of human-centered skills, including judgment, empathy, and conflict resolution.
- Designing the Human-in-the-Loop Architecture
- The Human-in-the-Loop (HITL) Integration Matrix: Establish clear boundaries between automated processes and required human oversight
- Information Sorting v. Third Ear Interpretation
- Scenario Simulation v. Empathetic Delivery
- Process Automation v. Ethical & Moral Reasoning
- Combating Hyperactive Connectivity: Draw on Cal Newport’s Deep Work and Slow Productivity to reduce cognitive fragmentation and improve decision quality.
- The Structural Anti-Backlash Framework: Move beyond performative compliance to address localized workplace conflict through human context.
- The KARR Training Method: Use a sustainable adult-learning mode (Knowledge, Application, Reinforcement, Resolution) for embedding compliant practices.
- The Human-in-the-Loop (HITL) Integration Matrix: Establish clear boundaries between automated processes and required human oversight
- Ramifications for Today and Tomorrow
- Moving From Transactional Control to Partnerships: Redefine organizational success through sustainable, human-centered systems.
- Escaping the Feedback Loop: Restore human agency through intentional oversight and leadership development.
- Practical Tools for Immediate Use:
- Open-access toolkit at https://www.ThirdEarCR.com/UnsustainableBook-Tools
- Pre-Assessment Safety Audit for profiling tools
- PARR Systemic Sustainability Matrix
- Questions & Answers (As Time Permits)
This webinar is divided into section summaries, which you can scan for key points and then dive into the sections that interest you the most.
Please note this AI-generated summary provides a general overview of the webinar but may not capture all details, nuances, or the exact words of the speaker. For complete accuracy, please refer to the original webinar recording.
Third Ear Conflict Resolution
Nance L. Schick, Esq. is a New York employment attorney, workplace mediator, and founder of Third Ear Conflict Resolution. With more than 20 years of experience, she advises organizations on workplace conflict, compliance, and the legal risks of emerging technologies, including algorithmic management and AI. Read More ›
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Status: Approved
Format: On-Demand
Credits: 1.00 General
Earn Credit Until: December 31, 2026
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 General
Earn Credit Until: August 13, 2031
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 Technology in the Practice of Law
Earn Credit Until: June 30, 2028
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 General
Earn Credit Until: August 13, 2028
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 General
Earn Credit Until: August 13, 2028
Status: Approved
Format: On-Demand
Credits: 1.00 General
Earn Credit Until: December 31, 2026
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 Substantive Law, Practice, and Procedure
Earn Credit Until: August 13, 2028
Status: Approved
Format: Live (Virtual), On-Demand
Credits: 1.00 General
Earn Credit Until: August 14, 2031
This presentation is approved for one hour of General CLE credit in Alabama, one hour of General CLE credit in Alaska, one hour of Technology in the Practice of Law CLE credit in California, one hour of General CLE credit in Hawaii, one hour of General CLE credit in Illinois, one hour of General CLE credit in Ohio, one hour of Substantive Law, Practice, and Procedure CLE credit in Pennsylvania, and one hour of General CLE credit in Vermont.
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