The Responsible AI Bulletin #14: AI value chains, collaborative clinical decision-making, and design space of GenAI models.

Welcome to this edition of?The?Responsible AI Bulletin, a weekly agglomeration of?research developments?in the field from around the Internet that caught my attention - a few morsels to dazzle in your next discussion on AI, its ethical implications, and what it means for?our future.

For those looking for more detailed investigations into research and reporting in the field of Responsible AI, I recommend subscribing to the?AI Ethics Brief, published by my team at the?Montreal AI Ethics Institute, an international non-profit research institute with a mission to democratize AI ethics literacy.

The Ethics of AI Value Chains: An Approach for Integrating and Expanding AI Ethics Research, Practice, and Governance

AI ethics principles and practices often fail to prevent many societal and environmental harms. In response, many researchers have called for AI ethics to be re-centered around new principles or conceptual focal points such as design practices, organizational practices, or relational structures. In this paper, we respond to those calls by presenting an ethics of AI value chains that overcomes the limitations of many current approaches to AI ethics. By re-centering our ethical reasoning around the value chains involved in providing inputs to and receiving outputs from AI systems, we can more broadly account for and intervene in a wider range of ethical concerns across many actors, resources, contexts, and scales of activity.

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Understanding the Effect of Counterfactual Explanations on Trust and Reliance on AI for Human-AI Collaborative Clinical Decision Making

Advanced artificial intelligence (AI) and machine learning (ML) models are increasingly being considered to increase efficiency and reduce the cost of performing decision-making tasks from various types of organizations and domains (e.g., health, bail decisions, child welfare services, etc.). However, users might place too much trust in the AI/ML system and even agree with ‘wrong’ AI outputs, and they achieve worse performance than humans or AI/ML models alone.

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The Design Space of Generative Models

Card et al.’s seminal paper “The Design Space of Input Devices” established the value of design spaces and similar ontologies for analysis and invention. In this position paper, we seek to advance discussion and reflection around the marriage of HCI and emerging generative AI models by proposing two design spaces: one for HCI applied to generative models and one for generative models applied to HCI. We hope these frameworks spark additional research in further refining these taxonomies and spurring the development of novel interfaces for generative models and novel AI-powered design and evaluation tools for HCI broadly.

Our first design space considers the application of HCI to generative AI models. The interfaces designed for interacting with such models have the potential to influence who can use the models (e.g., ML engineers vs. general users), model safety (e.g., supporting identification or interrogation of undesired outputs), and model applications (e.g., by altering the time and effort involved in prompt engineering). Our proposed taxonomy considers both the design possibilities for interfaces for providing input to models and those for presenting model outputs.

Generative models’ increasing variety and power will fundamentally change HCI research and practice by enabling a new generation of assets, tools, and methods. These artifacts will impact the full spectrum of HCI, including new tools to support design through creative ideation, new tools to build rapid prototypes of novel, interactive experiences, and new tools to support the evaluation of interfaces and ecosystems, such as through simulation. Our second design space illustrates the myriad ways in which generative AI can impact the practice of HCI.

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Comment and let me know?what you liked and if you have any recommendations on what I should read and cover next week. You can learn more about my work?here. See you soon!