Open||Source||Data

Join Charna Parkey as she recaps a transformative year in AI, exploring the delicate balance between innovation and ethics. From open source communities to global regulations, discover how trust, diversity, and collaboration are shaping the future of technology.

Vinay Kumar discusses the transformation of AI in banking and financial services, addressing challenges and solutions with regulatory compliance and model explainability while addressing the stringent requirements in the financial industry.Episode QuotesVinay Kumar"I always believe in this: you don't need to solve a very large problem. Maybe it will take a lot of time to do that. A lot of resources to do that but something small, which you can have an opportunity to solve that could be very big or a fundamental for quite a bit is fantastic. Think of a scenario where your small fundamental idea is a base for another small fundamental idea for someone else." Charna ParkeyWe also want to ground it a little bit in impact we've been seeing. And I think in the financial, banking, insurance industries it's not, I would say, an even distribution of advancement. Different countries have different regulations and different appetites for risk."Timestamps- [00:00:00] Introduction by Charna Parkey.- [00:01:57] Vinay Kumar begins talking about his journey.- [00:05:27] Discussion on building a search engine for STEM researchers.- [00:07:06] Challenges with early deep learning.- [00:09:55] Conversation shifts to ML observability.- [00:17:06] Discussion on simplifying verticalized AI.- [00:22:30] Impact of large language models (LLMs) on AI.- [00:30:58] Comparison of autonomous cars with AI regulation.- [00:37:58] Vinay mentions his science fiction novels.- [00:42:19] Conversation summary with Producer Leo Godoy.

Brian Magerko, an AI expert with a focus on co-creating experiences, discusses the challenges of AI literacy and public perception. He emphasizes the importance of trust and accountability in AI systems. The conversation highlights the creative potential of AI in projects like LuminAI and EarSketch, designed to bridge gaps in technology education for underrepresented groups. The need for interdisciplinary collaboration to ensure beneficial AI advancements is also explored, showcasing how art and technology can work hand in hand for a better future.

Heather Domin, an expert in AI governance and ethics, shares her insights on the urgent need for ethical practices in AI development. She highlights the role of the open-source community in fostering transparency and responsible AI usage. Domin discusses the transformative potential of generative AI, advocating for adaptive governance frameworks. The conversation touches on the significance of red teaming in AI risk mitigation and the delicate balance between addressing public fears and fostering hope, particularly for marginalized communities.

Ethan Soloviev, Chief Innovation Officer at HowGood, reveals how generative AI can revolutionize the food and agriculture industry. Discover the potential of AI to create a regenerative, sustainable, and net-positive food system that benefits the planet and all living beings.Timestamps1. Introduction and Background (00:00:00 - 00:01:16)2. Ethan's Journey (00:01:16 - 00:05:12)3. The Role of Food and Agriculture (00:05:12 - 00:06:52)4. Investment in Regenerative Agriculture and Generative AI (00:06:52 - 00:07:44)5. Levels of AI Impact (00:07:44 - 00:12:42)6. HowGood's Use of AI (00:12:42 - 00:13:20)7. Consumer Impact and Corporate Responsibility (00:13:20 - 00:15:44)8. Future of AI in Food Systems (00:15:44 - 00:20:30)9.  Innovative Perspectives on AI Training (00:20:30 - 00:21:10)10. Action models in agriculture, optimizing water and soil use on a larger scale. (00:24:14 - 00:25:28)11. Discussion on integrating human cultural geography into AI models. (00:27:37 - 00:30:00)12. Charna and Ethan discuss procurement decisions and their impact on sustainability. (00:30:20- 00:40:15)13. The ethical implications of AI in corporate and government decision-making. (00:42:01 - 00:54:31)14. Leo brings up the impact of AI on consumers, discussing how AI can change purchasing decisions by highlighting product sustainability. (00:54:40 - 00:55:30)15. Charna elaborates on using AI to understand different business models and how generational changes affect consumer choices. (00:55:47 - 00:57:32) QuotesEthan Soloviev"What if we're using ecological data? What if we're training on trees and insects and animals and whale song? What kind of questions would a gen AI trained on whale song and hummingbird language ask us?"Charna Parkey"If we have this great translator that is Gen AI, we already have text and language to code. We can do code generation. We can already interpret this code and tell me what it's going to do. Take that code to language. Why can't we do that with some of these other senses and these other measurements?"Connect with EthanConnect with Charna

 Beth Rudden, recognized as one of the 100 most brilliant leaders in AI ethics, discusses the crucial role of explainability and traceability in building trustworthy AI systems. She shares how Bast AI is using ontologies and knowledge graphs to provide contextual relevance and understanding, enabling humans to fully trust artificial intelligence and how it allows the system to transform fields like education and healthcare.Timestamps00:00:00 - Intro00:02:00 - Beth’s Journey00:19:33​ - Ontologies in AI00:21:44 - Data Lineage and Provenance00:32:52 - Open Source Tools00:38:38​ - Explainable AI00:44:58- Inspiration from NatureQuotesBeth Rudden: "The best thing that I could tell you that I see is that it's going to shift from more pure mathematical and statistical to much more semantic, more qualitative. Instead of quantity, we're going to have quality."Charna Parkey: "I love that because I've been so mathematical for most of my life. I didn't have a lot of words for the feelings or expressions, right? And so I had sort of this lack of data and the Brené Brown reference you make, like I have many of her books on my shelf and I often pull, I don't even know where it is right now, but the Atlas of the Heart because I am having this feeling and I don't know what it is."LinksConnect with BethConnect with Charna

Learn how Andrea Brown, CEO of Reliabl, is revolutionizing AI by ensuring diverse communities are represented in data annotation. Discover how this approach not only reduces bias but also improves algorithmic performance. Andrea shares insights from her journey as an entrepreneur and AI researcher.  Episode timestamps(02:22) Andrea's Career Journey and Experience with Open Source (Adobe, Macromedia, and Alteryx)(11:59) Origins of Alteryx's AI and ML Capabilities / Challenges of Data Annotation and Bias in AI(19:00) Data Transparency & Agency(26:05) Ethical Data Practices(31:00) Open Source Inclusion Algorithms(38:20) Translating AI Governance Policies into Technical Controls(39:00) Future Outlook for AI and ML(42:34) Impact of Diversity Data and Inclusion in Open SourceQuotesAndrea Brown"If we get more of this with data transparency, if we're able to include more inputs from marginalized communities into open source data sets, into open source algorithms, then these smaller platforms that maybe can't pay for a custom algorithm can use an algorithm without having to sacrifice inclusion." Charna Parkey“I think if we lift every single platform up, then we'll advance all of the state of the art and I'm excited for that to happen."Connect with AndreaConnect with Charna

In this week’s episode, Charna welcomes Asa Whillock, the VP & GM Machine Learning and Artificial Intelligence at Alteryx. Asa shares a surprising perspective on AI regulation, explaining how it sets a baseline for responsible practices. Discover why he believes regulation is crucial in guiding the ethical development and deployment of AI and learn the importance of continuous learning and what the past can teach us about navigating the challenges and opportunities of AI today. Episode timestamps(01:47)  Asa Whillock's career journey at market-leading companies and the role of open source in each (Adobe, Macromedia, Alteryx)(04:56) Feature Labs acquisition by Alteryx and its open source roots in democratizing machine learning capabilities(11:00) Survey findings on enterprise board members' perspectives on AI and the need to move beyond policy creation to implementation and governance.(27:00) Applying AI capabilities and decision-making related to AI  (30:00) The future of AI predominance, including cost reduction, open source model advancements, and the push for demonstrating business value(43:33) Advice for navigating AI expertise and decision-making, including continuous learning, self-awareness of decision-making models, and acknowledging knowledge limitsQuotesAsa Whillock"I love regulation. I think it's great. And people are like, what? Why would you say that? And the reason why I say that is because I think it puts a floor underneath all of us of what do we think good looks like?"Charna Parkey"I think we need to, as a community, focus on meeting them where they are if we really want the democratization that is promised. Yeah, I don't know any other way to do it."  

Join Charna Parkey as she interviews Robbi Armstrong, AI Products and Strategy Director at KeyBank. Discover how this $190 billion bank is navigating the rapidly evolving landscape of generative AI, balancing the need for innovation with the challenges of managing risk in a heavily regulated industry. Explore the impact of KeyBank's virtual assistant, MyKey, on client experience. With nearly 70% repeat usage, MyKey seamlessly transfers clients to contact center agents, providing a warm handoff that includes authentication and chat context. Episode Timestamps(02:11): Robbi Armstrong's role at KeyBank and intersection with open source and AI initiatives in the financial industry(04:06): Compliance and regulatory trends in AI for banking(12:10): Organizational Change Management with AI(28:00): Responsible and Ethical AI(37:00): Financial Literacy and AI QuotesRobbi Armstrong“I truly believe that if you are an organization and you are sitting back and you're not organizing a team and you're not organizing a program and you're not learning, you're not looking at education, you're not looking at change management around Gen AI, I don't think you'll be here in two years. I really truly believe that. Because you won't be able to compete."Charna Parkey“I think the democratization is real and I think it's incredibly important because that step in between the domain expert and the technology is very lossy. You know, oftentimes we say, well, if only I had the data to answer your question let me give you a different answer or let me answer it completely and now we can actually put it in the hands of the experts and say, well, oh, then let's go collect that data." LinksConnect with RobbiConnect with Charna  

Amanda Brock's path began with picking potatoes at 8 years old. Now, she's the CEO of OpenUK, advocating for open source across the UK. In this insightful interview, Brock shares her journey into open source law and policy. She dives into OpenUK's latest research on the state of open technology in Britain, talent challenges, and the economic impact of open source contributions. Brock also unpacks key discussions from State of OpenCon 2024 on open data, generative AI, and balanced regulation. Episode timestamps(05:06): State of open source in the UK  (07:22): Importance of open source community  (15:19): Balancing openness and regulation in AI  (21:19): Pace of technological development and regulation(28:21): Reliability and discernment with AI outputs(35:24): Universal advice QuotesAmanda Brock“I think the governments that are going to win, the governments that are going to have the best regulation that promotes most innovation are going to be the ones which are able to make their regulatory environment flow in the same way as the technology evolution and innovation flows."Charna Parkey"I think the expectation needs to change. Part of what has happened with, you know, literal text search or keyword search and just Google and things like that, is that the average person expects what comes back to be relatively factual. That it's been referenced and, you know, backlinked, etc. That's a deterministic system. These are not. These are based upon statistical likelihoods of what word should come next." LinksConnect with CharnaConnect with Amanda