Minute to Midnight

Does This Title Grab Your Attention?

Welcome to the metaverse. But not the Marvel one, or the Facebook one. More like a podcast about making a podcast? We exist in an attention economy where value comes from the length of engagement with digital content. Ben Moorman, Staley Zheng, and I discuss how our roles as internet users and content creators shape our interactions in the digital and material world. Much of our conversation revolves around the actual process of making podcasts, like this one, engaging for an audience. Personally, I struggle with the tension I feel contributing content to a media ecosystem that cultivates disinformation and feeds on polarization. Just as social media companies design their platforms to keep users online, I strive to retain listeners for as long as possible by shaping a message to be more compelling. Just as advertisement companies find new spaces to infiltrate with ads, I use our social media to grow our audience. Now obviously this platform is far too small to make any observable impact, but quickly you can see how an ecosystem of users and creators with similar motivations can lead to the media hellscape we navigate every day. How can it be that a tool meant to connect people can render us isolated? How can unlimited access to knowledge lead to information silos and rigid worldviews? It seems that many of the most beautiful powers of the internet are becoming increasingly difficult to access due to excessive noise and confusion. Simultaneously, some of the most powerful AI tools are now publicly available to anyone with an internet connection. At this strange inflection point, I think it is necessary to have conversations that reconsider the architecture of the internet and our online behaviors to imagine a future that harnesses the power of new technologies like AI to promote accessible information, data privacy, and digital autonomy. We only begin to scratch the surface of these massive questions, but this episode along with the two previous installments of this series build a basis for which to explore issues related to our shared digital future. If you are actually reading this right now and have any opinions on the potential success or failure of Web 3.0, please email me at 11.59.pod@gmail.com [//11.59.pod@gmail.com ]as I'd really love to dig into the technical side of this conversation in a future episode. Follow us on Instagram @11_59_pod [https://www.instagram.com/11_59_pod/?hl=en] **That one emoji 🤦‍♀️** References: "Facebook will push you to read articles before you share them" - Vox [https://www.vox.com/2021/5/10/22429240/facebook-prompt-users-read-articles-before-sharing] "What is GDPR, the EU’s new data protection law?" - EU [https://gdpr.eu/what-is-gdpr/] "AI art tools Stable Diffusion and Midjourney targeted with copyright lawsuit" - The Verge [https://www.theverge.com/2023/1/16/23557098/generative-ai-art-copyright-legal-lawsuit-stable-diffusion-midjourney-deviantart] "The current legal cases against generative AI are just the beginning" - Tech Crunch [https://techcrunch.com/2023/01/27/the-current-legal-cases-against-generative-ai-are-just-the-beginning/]

Evaluating the Conflict Within Effective Altruism

This episode is a continuation of our series on AI and data with guests Ben Moorman and Stanley Zheng. Although grounded in a discussion of machine learning technology, this episode ventures into complicated moral and ethical questions regarding our AI future such as: What is the greater good? What do we owe the future? Are we in a simulation? I can't guarantee any satisfying answers, but these questions help to guide our discussion of Effective Altruism and the controversy related to the means by which some in this community use to reach their goals. Much of this episode deals with the highly speculative and obscure nature of the distant future and the consequences related to our decisions today. Alternatively, this whole trajectory of technology may have played itself out already and now we are just living in a controlled simulation of an ancestorial planet. Who knows??? Lastly, you probably noticed the shaggy looking guy in the cover art. If you didn't know, that is Sam Bankman-Fried (SBF), and until about a month ago he was one of the most politically influential billionaires in the US. Now he is bankrupt and facing a slew of criminal charges after his company FTX collapsed last month. He is at the center of a lot of our conversation. The story is still developing, but in case you are interested I've included a link [https://docs.google.com/document/d/1-MsNBkEXq2lCwRGpyUBRQKxUXivbPjrRIPzat9sLH50/edit?usp=sharing] to the resources I used to prepare for this show with several helpful articles covering the simulation argument, Effective Altruism, and SBF. As always feel free to email us as 11.59.pod@gmail.com [//11.59.pod@gmail.com] with questions or concerns. Further, follow us on Instagram @11_59_pod [https://www.instagram.com/11_59_pod/?hl=en] to join the conversation through interactive content.  P.S. If you thought our theme music was groovy check out Mosant [https://open.spotify.com/artist/7IEEU0XVo4tSCEhoKVsG9W?si=akKoqkZxQcSjRGkjHEe7xg] on Spotify. Or go listen to them preform their single 'Critical' [https://open.spotify.com/track/2FPYnBtn0YeQgMA2VUuJDN?si=19e353929bfc45b5] at a Cincinnati venue near you!

Exploring the Relationship of Humans and AI

I join Ben Moorman and Stanley Zheng to discuss the architecture of machine learning models and the ethical responsibilities of the programmers that build them. This episode is the first in a 3-part series on data and its implications from the perspective of both programmers and users. We focused our conversation on bias in terms of human prejudice as well as its technical function in machine learning models. If you have ever felt perplexed by the vast and confusing landscape of AI this is s great opportunity to introduce yourself to foundational concepts with clear explanations, real-world examples, and broader contextualization. Here [https://docs.google.com/document/d/16RSWOVt716C6hjA7aXcKKPTvSSPlWoGy7SEDeD2MKIo/edit] is a link for the resources that introduced me to the terminology and methodology of concepts related to machine learning. Check out our Instagram for opportunities to join the conversation @11_59_pod [https://www.instagram.com/11_59_pod/?hl=en] or email us at 11.59.pod@gmail.com [//11.59.pod@gmail.com]

Finding a Place and Purpose in Politics

It's election day in America, so I sat down to have a conversation with Political Economy graduate student, Evan Eskilson. We discussed the challenges of finding our place in an overwhelming political landscape, the tools of partisan hegemony, and how to combat apathy towards a flawed democracy. This episode was a great way to initiate a dialogue with our audience that will extend beyond each episode. Enjoy!  If you have any questions or concerns reach out to us on Instagram @11_59_pod [https://www.instagram.com/11_59_pod/?hl=en] or email us at 11.59.pod@gmail.com [//11.59.pod@gmail.com]   Key Resources:  Evan Eskilson - "The Failure, Impossibility, and Dystopia of Green Growth"  [https://docs.google.com/document/d/1RjYo2Hl84Xyaou_VRcPpp-kX_cc3zWlCqUR_Kjc5Y0I/edit?usp=sharing] Benjamin Wallace-Wells - "How a Conservative Activist Invented the Conflict Over Critical Race Theory"  [https://www.newyorker.com/news/annals-of-inquiry/how-a-conservative-activist-invented-the-conflict-over-critical-race-theory] Gallup - American's Attention to National Political News [https://news.gallup.com/poll/357398/political-news-receiving-heightened-public-attention.aspx]  Oregon Governor's Debate 2022 [https://www.youtube.com/watch?v=x5wOshUChG8]