Objectives:

• Identify: Describe proposed AI solutions and potential ethical concerns.
• Evaluate: Gain immediate and in-depth ethical feedback on your solution.
• Develop: Craft solutions to mitigate identified ethical challenges.

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Materials:

• This template
• Markers or pens
• Flipcharts or whiteboard
• Sticky notes
• Optional: Laptops or tablets for individual work and research

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Timing: 2 hours, with flexibility for breaks and discussions.

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Instructions:

1. Introduction (15 minutes)

• Welcome participants and introduce yourself/your team.
• Briefly explain the purpose of the workshop and its objectives.
• Highlight the importance of ethical considerations in AI development.

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2. Solution Showcase (5 minutes)

• Individual Work: Participants work individually to describe their proposed AI solution in detail, either visually (e.g., diagrams, sketches) or in writing. Encourage them to be clear, concise and specific about the solution's purpose, functionality and target audience.
• Sharing and Discussion: Participants present their solutions to the group, using their visuals or written descriptions. Encourage questions and discussion to gain initial understanding and identify potential ethical concerns.

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3. Instant Ethical Feedback (25 minutes)

• Divide participants into small groups. Each group reviews 2-3 presented solutions, focusing on immediate ethical concerns that stand out. Encourage them to consider questions like:

1. Does the solution raise any privacy or data security issues?

2. Could it perpetuate or amplify existing societal biases?

3. Does it unfairly impact specific groups or individuals?

4. Are there transparency concerns regarding how the AI operates?

• Group Feedback: Each group shares their identified concerns with the person who initially proposed the AI solution, suggesting potential ethical resolutions or areas for further exploration. Encourage open and constructive dialogue.

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4. Thoughtful Ethical Feedback (20 minutes)

• Individual Reflection: Participants individually reflect on the feedback received and consider additional ethical challenges their solution might present. Encourage them to delve deeper into areas like:

1. Explainability and interpretability of the AI's decision-making.

2. Potential for unintended consequences or negative impacts.

3. Alignment with ethical principles like fairness, accountability, and non-maleficence.

• Group Brainstorming: Re-form small groups and brainstorm specific mitigation strategies for the identified ethical challenges. Encourage them to consider:

1. Design modifications to the solution.

2. Ethical guidelines and oversight mechanisms.

3. Data collection and usage practices.

4. User education and awareness initiatives.

• Sharing and Discussion: Each group shares their proposed mitigation strategies with the larger group, fostering discussion and peer-to-peer learning.

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5. Granular Examination (60 minutes)

• Focus Areas: Divide the group into four stations, each focusing on a specific ethical concern:

1. Bias: Discuss potential sources of bias in the solution's development, data and algorithms. Brainstorm mitigation strategies like diverse data sets, fairness checks and human oversight.

2. Data Privacy: Discuss data collection, storage and usage practices. Explore user control mechanisms, anonymisation techniques and transparency measures.

3. Accuracy: Evaluate the solution's accuracy and potential sources of error. Discuss strategies to ensure reliability, data quality, and continuous testing and improvement.

4. Transparency: Discuss the level of transparency offered by the solution regarding its decision-making process. Explore explainable AI techniques, user feedback loops, and educational resources.

• Rotation and Discussion: Participants rotate through all stations, engaging in focused discussions and brainstorming mitigation strategies for each ethical concern.
• Final Sharing: Each station shares key insights and proposed solutions with the entire group, fostering a comprehensive understanding of the solution's ethical landscape.

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6. Wrap-up and Next Steps (15 minutes)

• Summarise the key takeaways from the workshop: identified ethical concerns and mitigation strategies for different types of AI applications.
• Encourage participants to continue refining their solutions with ethical considerations in mind.
• Share resources for further learning and support on responsible AI development.
• Celebrate the collaborative effort and emphasise the importance of ongoing ethical evaluation and improvement.

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Additional Tips:

• Adapt the level of detail and complexity based on the participants' expertise and the specific AI solutions under discussion.
• Encourage active participation, open dialogue, and respectful debate throughout the workshop.
• Use case studies or real-world examples to illustrate key ethical concerns and potential solutions.
• Be mindful of time management and adjust the schedule as needed.