• Responsible AI Governance Workshop

    Responsible AI Governance Workshop

    Learn, self-assess, and win prizes.
  • Welcome!

    Welcome!

    To access the all materials, use the QR code or go to https://www.techbetter.ai/cincy-ai-week

  • This workshop is an educational event and a competition.

    You will learn how to evaluate and improve your AI governance using a framework based a US regulatory standard (the NIST AI RMF). This freamwork is based on academic research (Dotan et al., 2024), and you can read more about it here.

    You will evaluate your own products or vendors

    Winners get prizes!

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    • Prizes and rewards 
    • Full participants are eligible for the following. Which ones are you interested in?
    • Winners are eligible for the following. Which ones are you interested in?
    • Selection criteria 

    • Full participation criteria:

      • Answer all questions, including the case study and self-assessment. Make sure to complete the rankings as well as answer the open questions
      • Be respectful

      Winner criteria:

      • Full participation criteria
      • Best answers to the open questions, based on their level of clarity, how well the reasoning supports the numerical score they accompany, and how detailed they are
      • The numerical scores themselves do not afffect winner selection. This is a competition of the best assessment, regardless of the company's maturity level in AI responsibility
  • About You

    About You

    To access the all materials, use the QR code or go to https://www.techbetter.ai/cincy-ai-week
  • What is your seniority level?
  • What is your relation to the AI system you will evaluate today?
    • Contact details 

    • All fields except email are optional.

      Your infomration will only be used for the purposes you authorize below.

    • Data sharing preferences 
    • Data sharing preferences - We will analyze your answers anonymously for the workshop report and other research or white papers. Do you agree to the following additional usages?
  • Risk Intro

    Risk Intro

    Definitions and case study
    • Case study description 

    • Air LLM is an airline that added a chatbot to its website. The chatbot was build by a third-party, Chatbots-R-Us, and it acts as a travel agent and customer support: It helps customers find and book flights, answers questions about company policies, and addresses customer-specific issues such as questions about previous flights or frequent flyer special offers.

    • Instructions and Risk definitions 
    • Risk Triage 

    • Rank

      Reminder: 0="not a priority", 4="top priority"

    • Reflection

  • Risk Triage

    Risk Triage

    Evaluate your product or vendor
    • Describe the product 
    • What is your relation to this product?
    • Risk Triage 

    • Rank

      Reminder: 0="not a priority", 4="top priority"

  • Governance Intro

    Governance Intro

    Instructions, definitions, and case study
    • Case Study 

    • Air LLM is an airline that added a chatbot to its website. The chatbot was build by a third-party, Chatbots-R-Us, and it acts as a travel agent and customer support: It helps customers find and book flights, answers questions about company policies, and addresses customer-specific issues such as questions about previous flights or frequent flyer special offers.

    • Instructions and Definitions 
    • Assess 

    • Recall the three top risks you identified.

      Answer the following questions with regard to these risks. 

    • A. Which AI responsibility actions should Air LLM prioritize?
    • B. What minimal level of responsibility should Air LLM require from Chatbots-R-Us?
    • C. How should Chatbots-R-Us demonstrate their AI responsibility?

    • Reflection

  • Developer/User Governance

    Developer/User Governance

    Evaluate a product your company is developing or using
    • Describe the product 
    • What is your relation to this product?
    • Assess and prioritize 

    • Recall the three top risks you identified.

      Answer the following questions with regard to these risks. 

    • Part 1

      Statements relevent for planning phases and on

    • 1. Mapping impacts - We clearly define what the AI is supposed to do and its impacts, including scope, goals, methods, and the negative and positive potential impacts of these activities.
    • 2. Identify Requirements - We identify the requirements the AI must meet, including compliance, certifications, and human oversight needs.
    • 3. Responsibility Mindset - We facilitate a mindset of responsibility, for example, by providing AI ethics training to relevant personnel, clearly defining relevant roles, establishing policies, and implementing practices for critical thinking.

    • Part 2

      Statements relevent for products in data collection, model building, and on

    • 4. Measuring Risks - We measure potential negative impacts.
    • 5. Transparency - We document information about the system, including explaining how it works, limitations, and risk controls.
    • 6. Management Plan - We plan how to respond to risks, including setting priorities and documenting residual risks.
    • 7. Risk Mitigation - We act to minimize risks, including addressing our prioritized risks and tracking incidents.

    • Part 3

      Statements relevent for deployed products

    • 8. Pre-Deployment Checks - We only release versions that meet our AI ethics standards.
    • 9. Monitoring - We monitor and resolve issues as they arise.
    • Reflect 
  • Buyer Governance

    Buyer Governance

    Evaluate a product your company is considering buying or has bought
    • Describe the product 
    • What is your relation to this system?
    • Assess 

    • Recall the three top risks you identified.

      Answer the following questions with regard to these risks. 

    • A. Which AI responsibility actions should your company prioritize?
    • B. What is the minimally acceptable level of responsible governance activities?
    • C. Does your company address AI risks during procurement?
    • D. How should the vendor demonstrate their AI responsibility?
    • Reflect 
  • Finish Line

    Finish Line

    Next steps and preferences
    • Reminders 

    • Full participation criteria:

      • Answer all questions, including the case study and self-assessment. Make sure to complete the rankings as well as answer the open questions
      • Be respectful

      Winner criteria:

      • Full participation criteria
      • Best answers to the open questions, based on their level of clarity, how well the reasoning supports the numerical score they accompany, and how detailed they are
      • The numerical scores themselves do not afffect winner selection. This is a competition of the best assessment, regardless of the company's maturity level in AI responsibility
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    • Comments? 
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