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X-WR-CALNAME:Regional Perspectives on AI
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X-WR-CALDESC:Events for Regional Perspectives on AI
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DTSTART;TZID=America/New_York:20260814T143000
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SUMMARY:Do We Still Need the Four‑Year Degree in the Age of AI?
DESCRIPTION:The accelerating integration of artificial intelligence into professional work raises fundamental questions about the continued necessity of the traditional four‑year college degree. A central finding of this analysis is that AI should be understood as a tool\, not a substitute for human judgment. Yet because AI tools evolve rapidly and are embedded within specific organizational workflows\, the expertise required to use them effectively is increasingly domain‑specific rather than general. This shift weakens the historical economic rationale for broad\, generalized undergraduate education. \nHistorically\, mastery of complex tools has been transmitted through apprenticeship systems\, not universities. Evidence from multiple countries suggests that AI is pushing workforce development back toward this model. The UK has expanded degree‑linked apprenticeships in digital and data roles; Germany integrates AI and automation into its long‑standing dual vocational system; Singapore’s AI Apprenticeship Programme embeds learners directly inside companies using proprietary datasets; and the U.S. government has begun approving registered apprenticeships in AI‑related fields. While promising\, these initiatives lack long‑term outcome data\, and their scalability remains uncertain. \nThe analysis distinguishes between the economic and self‑development functions of college. AI reduces the economic value of generalist degrees by automating many entry‑level cognitive tasks that once justified hiring bachelor’s‑level graduates. Only highly technical\, regulated\, or high‑stakes fields—such as medicine or engineering—retain a clear need for extended academic preparation. Meanwhile\, the self‑development benefits of college\, though still valuable\, do not inherently require a four‑year residential model. If higher education becomes primarily a self‑development institution\, its current cost structure is unlikely to remain viable. \nOverall\, the evidence suggests a hybrid future: apprenticeships \nSpeaker Biography\nDr. Michael K. Green is a Professor of Philosophy at SUNY Oneonta\, where he has taught since 1981 and earned promotion to full professor in 1995. He holds a PhD in Philosophy from the University of Chicago and a BA in Philosophy from the University of Kansas. His scholarship spans ethics\, philosophy of action\, political and social philosophy\, business ethics\, and the history of philosophy. His publications include How Do We Create a Philosophical Cosmos for Acting Socially and Being Happy? (2007) and the edited volume Issues in Native American Cultural Identity (1994)\, along with more than forty articles on topics ranging from moral psychology and cultural identity to economic ontology and institutional trust. \nDr. Green has presented nationally and internationally\, with peer‑reviewed talks in the United States\, Europe\, and Mexico\, including recent work on resilience\, emotional meaning in economics\, and cultural frameworks in philosophy. He has also developed numerous leadership case studies for the Hartwick Humanities in Management Institute. He has been recognized with the Susan Sutton Smith Award for Academic Excellence and the Technology Award.
URL:https://ai-symposium.openlab.oneonta.edu/event/do-we-still-need-the-four-year-degree-in-the-age-of-ai/
LOCATION:Morris Hall 104
CATEGORIES:Evolving AI Tools
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DTSTART;TZID=America/New_York:20260814T100000
DTEND;TZID=America/New_York:20260814T105500
DTSTAMP:20260804T182424Z
CREATED:20260804T181530Z
LAST-MODIFIED:20260804T182424Z
UID:247-1786701600-1786704900@ai-symposium.openlab.oneonta.edu
SUMMARY:AI Sandbox
DESCRIPTION:The AI Sandbox is not a presentation or workshop\, but rather a curated space where you can go to explore different AI tools. Volunteers from SUNY Oneonta’s Faculty Center and Milne Library have created handouts that list some tools to try\, and faculty and staff will be available to talk about AI\, integration into various programs and tools\, and the rapidly emerging tools available for research\, design\, and image and text generation. \nCome visit the AI Sandbox\, and feel free to drop by and pick up handouts even if you can’t stay.
URL:https://ai-symposium.openlab.oneonta.edu/event/ai-sandbox/
LOCATION:Le Cafe
CATEGORIES:Evolving AI Tools
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DTSTART;TZID=America/New_York:20260814T100000
DTEND;TZID=America/New_York:20260814T102500
DTSTAMP:20260714T153251Z
CREATED:20260708T205905Z
LAST-MODIFIED:20260714T153251Z
UID:173-1786701600-1786703100@ai-symposium.openlab.oneonta.edu
SUMMARY:Preliminary Investigations of Transformer Models for Bit-Domain Audio Synthesis and Timbre
DESCRIPTION:I will be presenting on preliminary research findings of new work centered on the associations between Bit-Domain Audio Synthesis and timbre generation. Bit-Domain Audio Synthesis describes a class of techniques in which PCM audio samples are produced by closed-form integer expressions. These techniques include arithmetic and bitwise operations evaluated against an incrementing sample index. For example\, the expression “t * (t >> 5 | t >> 8)”\, in which the index t is combined with itself via right-shift\, bitwise OR\, and multiplication\, produces sustained tonal material with evolving timbral character. This presentation reports on early experiments using compact autoregressive transformer models as discovery instruments for the relationship between expression structure and timbral outcome\, trained on bit expression/audio pairs. \nSpeaker Biography\nDaniel McKemie is a composer\, technologist\, researcher\, and percussionist based in Oneonta\, New York. His work focuses on audio feature extraction and low-level signal processing to explore timbre and novel synthesis techniques. Additionally\, he designs innovative methods for interfacing handmade circuitry\, controllers\, and embedded systems with custom software to achieve his musical results. This approach enables the creation of complex\, responsive performance environments and compositional processes controllable from multiple angles. \nDaniel currently serves as a Lecturer at SUNY Oneonta\, where he teaches courses on electronic music\, popular music\, percussion\, and music psychology. He earned his MS in Computer Science at Brooklyn College\, where he worked as a graduate research assistant in Professor Johanna Devaney’s Laboratory for Understanding Music and Audio (LUMaA)\, and served as an adjunct lecturer teaching courses in computer music. Daniel also has his MA in Music Composition from Mills College and BA in Music Performance from University of Nevada\, Las Vegas.
URL:https://ai-symposium.openlab.oneonta.edu/event/hearing-the-numbers-ai-as-a-tool-for-exploring-algorithmic-composition/
LOCATION:Morris Hall 104
CATEGORIES:Evolving AI Tools
ATTACH;FMTTYPE=image/jpeg:https://ai-symposium.openlab.oneonta.edu/wp-content/uploads/sites/583/2026/07/0037645002_10.jpg
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DTSTART;TZID=America/New_York:20260814T090000
DTEND;TZID=America/New_York:20260814T095500
DTSTAMP:20260709T133035Z
CREATED:20260708T211757Z
LAST-MODIFIED:20260709T133035Z
UID:179-1786698000-1786701300@ai-symposium.openlab.oneonta.edu
SUMMARY:From Dartmouth to Now: Headlines from AI History that Set the Stage for Today
DESCRIPTION:Welcome from the Regional Perspectives on AI Symposium Organizing Committee. Before the day turns to practical questions\, how AI is reshaping teaching\, research\, and administrative work across our campuses\, we want to pause and take stock of how we got here. This opening session walks through ten headline-making moments in AI history\, from the field’s founding claims at the 1956 Dartmouth workshop to today’s generative AI boom\, pairing each milestone with a short reflection on what it tells us about the choices in front of higher education now. This isn’t a comprehensive timeline; it’s a shared vocabulary-building exercise\, a chance to level-set a room with very different degrees of AI familiarity and to surface the patterns — hype cycles\, labor anxieties\, questions of trust and authorship — that connect decades-old debates to this year’s conversations. Attendees will leave with a common frame of reference for the sessions that follow\, and a sense that this year’s AI moment is one chapter in a much longer story than the news cycle usually suggests.
URL:https://ai-symposium.openlab.oneonta.edu/event/from-dartmouth-to-now-headlines-from-ai-history-that-set-the-stage-for-today/
LOCATION:Craven Lounge
CATEGORIES:Evolving AI Tools
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