AI, Agile, & Sustainability

Sprint 1

Team formation & definition of what AI and Agile is for the team. Creating the concept of Principles, Ethics and Practice.

We brainstormed on the question “what is the future of agile?”

Sprint 1 Review

Sprint 2

We analysed the current state. Which refined the sprint 2 goal.

From this we defined the future state definition.

Finally we established a set of 10 Principles for Agile, AI & Sustainability. Sprint 2 Review.

USER QUESTION

Considering how things have changed since the agile manifesto was thought of and what we know now. If a manifesto was created now taking into account ai, what would it be?

ChatGPT RESPONSE

A modern manifesto for AI development might include the following principles:

  1. Human-Centered AI: Prioritize AI solutions that enhance human well-being, safety, and privacy. Ensure AI systems are designed to benefit, empower, and protect individuals.
  2. Ethical AI: Commit to the ethical development and use of AI. Adhere to principles of fairness, transparency, accountability, and avoidance of bias.
  3. Continuous Learning: Embrace AI as an ever-evolving field. Foster a culture of continuous learning, adaptation, and improvement.
  4. Collaboration and Interdisciplinary Approach: Promote collaboration among diverse experts, including data scientists, ethicists, psychologists, and domain specialists to create well-rounded AI solutions.
  5. Accessibility and Inclusivity: Ensure AI technology is accessible to all and doesn’t discriminate based on abilities, demographics, or socioeconomic factors.
  6. Data Privacy and Security: Prioritize robust data protection and security measures to safeguard user information. Minimize data collection to only what is necessary.
  7. Transparency and Accountability: Maintain clear documentation of AI algorithms and decision-making processes. Hold developers and organizations accountable for AI outcomes.
  8. Environmental Responsibility: Consider the environmental impact of AI systems, including energy consumption and resource usage.
  9. Regulatory Compliance: Comply with relevant laws and regulations governing AI, and actively engage with policymakers to shape responsible AI policies.
  10. Public Education: Promote public understanding of AI and its capabilities, limitations, and potential impact on society.

These principles reflect the evolving landscape of AI and its integration into society while maintaining a commitment to human values, ethics, and responsible development. Keep in mind that creating a new manifesto would involve input from experts across various fields and stakeholders in the AI community.