The MERL Tech Initiative

Do you play a role advising senior leadership on GenAI and its implications? Join us for our next *in-person* Technology Salon (9-11am in New York City on March 11) where we'll focus on "How can we help Senior Leaders better understand AI?" As emerging artificial intelligence (AI) enters the mainstream, senior level leaders and decision makers are required to make critical policy and practice decisions about the development and use of these tools. However, high level leaders in government have been criticized for a low level of understanding of technology, social media, and algorithms. “The problem is that most lawmakers do not even know what A.I. is,” said the only member of Congress with a master’s degree in artificial intelligence. Humanitarian and global development agencies have similar challenges, including: --a growing concern over partnerships with AI companies --capture of data from vulnerable populations --testing of tools that use data from crisis-affected populations without clear and informed consent. Technical advisors play a key role in briefing decision-makers on what emerging technologies like Generative AI can and cannot do and -- perhaps more importantly -- when they should and should not be used. Yet senior leadership face multiple pressure points and are extremely short on time, making it difficult to ensure that they are fully informed on the implications of their decisions. This will be a closed-door conversation to explore strategies and tactics for keeping senior leadership well-informed on the implications of Generative AI and other emerging AI technologies Leading the discussion will be: Friederike Schüür, UNICEF’s Chief of Data Strategy and Data Governance Ronen Rapoport, UN Information Systems Specialist Conor Flavin, Senior Data Policy Officer at UNHCR Willmary Escoto, Esq. (CIPP/E), Access Now’s US Policy Counsel, AI and Data Privacy Mala Kumar, former GitHub Director of Tech for Social Good Brent O. Phillips, Humanitarian AI Today We’ll discuss: --What key challenges do advisors face when briefing senior leaders on policy and laying out the implications of emerging AI? --What are the competing influences that advisors should be aware of and how do they affect how decisions are made? --What strategies and tactics have worked to communicate clearly and effectively about the complexities of emerging AI? --What good practices can advisors share? This Salon is limited to 30 spots. It will be strictly off-the-record. RSVP now.

AI is an extractive economy. In addition to drawing on huge quantities of energy and water to run massive data centers, AI systems require the extraction of data from our bodies, our minds, our purchases, our art, our statements, our actions, and our locations to fuel their outputs. Last week I gave a talk on how Evaluators could use the “Just Transition” framework to explore what the transition to an AI economy might look like if done in a just and equitable way, with greater participation and accountability and respect for people and planet. AI is not just another tech tool -- it has big implications in terms of equity and inclusion, privacy, jobs, the environment, media and information integrity, and our societies. We need to unpack current AI narratives and the world views behind them if we are to understand AI trends in terms of where they come from, where they are going, and how they affect individuals and societies now and in the future. There is a great deal of interest in AI in the field of Evaluation, yet we are still mostly playing around at the edges. We should be exploring and unpacking AI at a systems level. Evaluators and evaluation societies should deepen their understanding of AI and its current and future implications. We have a role in contributing to a more just transition to the AI present and future. Here's a link to the slides and accompanying notes. ChatGPT/DALL-E generated some pretty amazing artwork for the slides!