This session for MSF Directors of Fundraising asked the following question: "How Might We… use generative AI to develop our growth mindset?". The session was practical, outlining the opportunity for Fundraising Directors to be more productive, efficient and effective in their day-to-day work by using generative AI tools. The main focus was ChatGPT, but the session also covered other AI tools and development.
1. Key definitions
2. Deep dive: ChatGPT
Tips and hints for prompting
Test example prompts
3. Risks and concerns around Generative AI
- Misuse for misinformation/disinformation - Generative AI can be misused to spread false or misleading information.
- Bias in outputted information - Generative AI can perpetuate biases present in the training data.
- Data privacy - The inputted data used to train generative AI models may be sensitive and require protection.
- Credibility and reputational risk - Misuse of generative AI can damage the credibility and reputation of individuals or organizations.
- Environmental impact of training and using LLMs - Training and using LLMs requires significant computing power and may have environmental impacts.
- Copyright of training data and produced outputs - Ownership and licensing of training data and produced outputs can be complex and require legal considerations.
- Reputational and credibility risks if misused - Misuse of generative AI can result in reputational and credibility risks for individuals or organizations.
4. Generative AI Tools database
6. Some suggested next steps
- Test some of the examples provided in this session and explore the capabilities of generative AI.
- Follow some AI influencers and stay up-to-date with the latest developments in the field.
- Identify users within your teams who could benefit from using generative AI tools and explore potential use cases.
- Develop safe spaces for experimentation in your team(s) and encourage innovation and creativity.