Summary of Towards Equitable Agile Research and Development Of Ai and Robotics, by Andrew Hundt et al.
Towards Equitable Agile Research and Development of AI and Robotics
by Andrew Hundt, Julia Schuller, Severin Kacianka
First submitted to arxiv on: 13 Feb 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computers and Society (cs.CY); Machine Learning (cs.LG); Robotics (cs.RO); Software Engineering (cs.SE)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary A machine learning (ML) and artificial intelligence (AI) framework is proposed to build organizational equity capabilities and better integrate evidence-based best practices. The existing ML and AI methods amplify biases and prejudices, as do robots with AI. A “culture of modularity” allows harms to be perceived as out-of-scope or someone else’s responsibility throughout the AI supply chain. Despite claims of equity, diversity, and inclusion (EDI) goals, few organizations respect peoples’ rights, recognize failures, or address them. The proposed framework adapts widely practiced R&D project management methodologies to build organizational equity capabilities. It organizes and operationalizes promising practices, skill sets, cultures, and methods to detect and address fairness, equity, accountability, and ethical problems early on. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary A new AI and ML framework is being created to make organizations more fair and equal. Right now, AI and ML systems often copy and make worse the biases and prejudices that exist in society. For example, facial recognition systems might not recognize black women as human beings. The people working on these systems don’t always take responsibility for their mistakes or try to fix them. This framework will help organizations be more equal by adapting how they work together to build new AI and ML systems. |
Keywords
* Artificial intelligence * Machine learning
