Tennessee State Scraps AI Bans, Ties Tenure to Tech Adoption

Panel 5-2 AI Policy Implementation Higher Education: A Case Study Organizational Change Tennessee — Ai4

Ai4

University bans fail because technology outpaces bureaucratic policy, requiring institutions to redesign coursework and credit AI scholarship in tenure reviews to secure adoption.

AI-assisted summary of Panel 5-2 AI Policy Implementation Higher Education: A Case Study Organizational Change Tennessee — original source. Check the original for full context.

Source published: 2026-08-14

Detailed notes

## Background Published on YouTube by Ai4 on August 14, 2026, this presentation features Dr. Robbie Melton, Vice President of SMART AI for ALL Applied Research & Innovations at Tennessee State University. According to the description, the session explores how higher education institutions serving underrepresented populations can transform AI policy from a compliance mandate into an adaptive, equity-driven framework for institutional excellence.

## TL;DR Dr. Robbie Melton addresses the recurring cycle of technological anxiety in academia, urging universities to abandon reactive bans in favor of dynamic 'AI in Action' living policies. Drawing on Tennessee State University's implementation experience, she advocates for redesigning assignments rather than policing software, emphasizing that AI misuse reflects outdated pedagogical design. Melton demonstrates practical applications through wearable technologies and consumer tools sourced from platforms like TikTok to enrich educational pathways. To achieve sustainable institutional adoption, she underscores the necessity of incentivizing faculty through tenure and promotion recognition while maintaining tight operational partnerships with IT infrastructure.

## Atmosphere & style Energetic, pragmatic, and richly humorous, Dr. Melton commands the stage with the seasoned charisma of a veteran educator who has navigated multiple tech revolutions. Her presentation balances lively audience engagement—such as debunking the color of yield signs and joking about smart shoes becoming 'snitchers'—with hard-nosed institutional strategy. The talk feels disarming and inspiring, effectively cutting through abstract generative AI hysteria to deliver grounded, real-world solutions for modern classrooms.

## Key takeaways - [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) Academic institutions often respond to technological disruptions with fear and outdated mental models, clinging to legacy assumptions just as drivers mistakenly believe yield signs are still yellow. - [02:56](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=176s) The default administrative reflex to ban generative AI mirrors past resistance to mobile phones, failing to harness computational power far exceeding what NASA used to reach the moon. - [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) Traditional university policy-making timelines are obsolete for emerging tech; spending a full year drafting rigid policies guarantees they will be outdated upon approval. - [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) A viable institutional AI framework ('AI in Action') must be an open-ended, dynamic living policy that includes often-overlooked stakeholders like administrative staff and procurement officers. - [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) Academic dishonesty is an age-old issue, not a unique product of LLMs; if an assignment can be completed effortlessly by AI, it signals a flaw in pedagogical design rather than a need for punitive bans. - [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) Most faculty and students are self-taught on free AI platforms without formal training, making structured and continuous professional development essential across all proficiency levels. - [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) AI applications extend far beyond desktop text generators into practical wearables, such as smart glasses and chemical-sensing nail polish engineered for personal safety. - [09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) Consumer platforms like TikTok serve as valuable incubators for educational tools, where testing emerging social media trends yielded an 82% adoption viability rate at TSU. - [11:48](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=708s) Combating algorithmic bias against underrepresented populations requires educators to proactively communicate with developers and actively train models using reinforcement feedback mechanisms. - [11:48](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=708s) Grant funding alone will not drive sustainable AI adoption unless institutions formally recognize AI integration and scholarship within tenure and promotion structures. - [11:48](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=708s) Deep operational alignment between academic leadership and campus IT is critical for technical safety, demonstrated by the ability to isolate and shut down a rogue campus AI tool within 8 minutes. - [14:42](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=882s) Theoretical governance documents are ineffective without an actionable implementation playbook that connects policy directly to pedagogy, student needs, and administrative infrastructure.

## Detailed walkthrough ### [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) The Hardest Job in Higher Education and the Yield Sign Paradigm

Dr. Robbie Melton introduces herself as a long-time educator who has traveled across many lands and institutions, facing what she calls "the hardest job in the world": convincing higher education faculty to embrace new technology. Having started her career well before the internet arrived on college campuses, she views the current panic surrounding artificial intelligence as part of a familiar cycle. She draws direct parallels between today's AI anxieties and the past disruptions of the "Internet of Everything" and the emergence of MOOCs (Massive Open Online Courses), when skeptics questioned how anyone could possibly learn online.

To demonstrate how stubbornly humans cling to outdated mental models, Dr. Melton conducts an immediate interactive exercise with the audience, asking them to shout out the color of a standard yield sign. When the room responds with "yellow," she reveals that yield signs have been red and white for over 45 years. She explains that people instinctively hold on to outdated knowledge even when reality has fundamentally shifted, using this metaphor to illustrate why academic institutions need ongoing collaboration and a mindset reset to navigate technological change.

```mermaid flowchart TD accTitle: TSU AI in Action Implementation Framework accDescription: Flowchart illustrating stakeholder integration, policy dynamism, pedagogy, and technical safeguards.

subgraph Stakeholders ["Stakeholder Inclusivity"] F["Faculty & Students"] A["Administrators & Procurement"] C["Broader Community"] end

subgraph LivingPolicy ["Living Policy: AI in Action"] P["Adaptive, Open-Ended Framework"] T["Tenure & Promotion Recognition"] end

subgraph PracticeSafeguards ["Pedagogy & Safeguards"] E["Redesigned Authentic Assessment"] IT["IT Partnership: Rapid Threat Neutralization"] end

Stakeholders --> LivingPolicy LivingPolicy --> PracticeSafeguards ```

---

[02:56](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=176s) From Moon Landings to Candy Crush: Shifting Away from the Ban Mentality

Addressing the role of institutional leaders during the AI transformation, Dr. Melton describes her primary mission as traveling the globe to "settle people down" by demystifying the *when*, the *why*, and the *how* of the technology. She holds up a smartphone and reminds the audience of the contentious debates from twenty years prior over whether mobile devices belonged in academic environments, noting that some individuals still resist by clinging to flip phones with extendable antennas.

She puts the computing power of modern hardware into sharp perspective: a standard smartphone holds exponentially more computational capacity than the systems NASA used to put a human on the moon. Yet, despite holding that monumental capability in their palms, society primarily uses smartphones to play casual games like *Candy Crush*—a single app that grossed over $1 billion. Dr. Melton argues that whenever academia fails to understand a tool's potential or operation, the default administrative reflex is simply to ban it, which is the exact trap universities are falling into with generative AI.

---

[05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) Building a Living Policy: "AI in Action" and Rethinking the Cheating Dilemma

Dr. Melton outlines the hurdles Tennessee State University (TSU) encountered when crafting their institutional AI policy. The process took an entire year because campus factions could not reach consensus; by the time the governing board officially approved the document, the underlying technology had already evolved past it. This experience underscored that any viable modern policy must be open-ended, dynamic, and inclusive of previously overlooked stakeholders, such as administrative staff, procurement officers, and the local community, creating a framework TSU calls "AI in Action."

Turning to the widespread panic over academic integrity, Dr. Melton challenges the idea that cheating is a novel problem brought on by modern large language models. Reflecting on her own academic journey writing a doctoral dissertation on a keypunch machine, she jokes that students have been finding ways to cheat since the era of *The Flintstones*. Rather than policing software, she argues that if an assignment can be bypassed effortlessly using AI, the instructor's pedagogical design is fundamentally flawed. As a tenured full professor, she asserts that ethical and legal AI use should be leveraged to elevate teaching and learning rather than driving educators toward punitive bans.

- **Policy timeline**: Took 1 full year to draft and gain board approval, highlighting the risk of static policies becoming obsolete upon release. - **Overlooked stakeholders**: Administrative personnel, procurement departments, and local community partners. - **Pedagogical stance**: If current coursework allows uncritical AI cheating, assignments must be redesigned to foster genuine critical thinking.

---

[07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) Wearable AI, Date-Rape Detection Nail Polish, and Practical Relevance

Dr. Melton highlights the widespread gap in formal AI education, observing that most faculty and students are self-taught on free tools like ChatGPT 3.5 without structured guidance. She stresses that even seasoned institutional "AI gurus" must continuously update their understanding because the technology is iterating rapidly beneath the surface.

To bring AI down to an accessible, human level, Dr. Melton showcases wearable technologies she personally tests. Displaying her AI-enabled smart glasses and chemical-sensing nail polish engineered to detect date-rape drugs in beverages, she illustrates how AI extends far beyond desktop text generators. While acknowledging valid macro-level concerns—such as the environmental footprint of AI data centers and misuse—she urges academic conferences to focus on evidence-based applications that directly enhance research, student health, and classroom productivity.

---

[09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) Rapid Tool Evolution, TikTok Sourcing, and Educational Pathways

Illustrating the breakneck pace of AI development, Dr. Melton notes that major platforms ship transformative upgrades on a daily basis, referencing same-day updates to Google Gemini and tools like Napkin AI for automated slide creation. She describes herself as an active evaluator and wearer of emerging tech, comparing the exploration of modern AI to the exploratory mission of the *Starship Enterprise*.

In an unexpected institutional strategy, TSU tracks emerging consumer technologies on TikTok—which Dr. Melton characterizes as the modern equivalent of early Kickstarter campaigns. The university established a dedicated review committee that purchases emerging tech and AI products discovered on social media to evaluate their educational viability. Dr. Melton reports that over 82% of the consumer tools they tested proved to be "on point" for integration into degree pathways and teacher education, demonstrating the value of meeting students where technology is naturally adopted.

---

[11:48](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=708s) Algorithmic Bias, Tenure Recognition, and "Dating" the IT Department

Dr. Melton discusses her proactive work on AI ethics and equity, recounting how she reached out directly to AI model developers two and a half years ago to challenge how poorly underrepresented demographic groups were represented in image and text generation prompts. She emphasizes that tech companies welcomed the critique, urging users to actively train and refine models by consistently using built-in reinforcement feedback buttons (thumbs up and thumbs down) to combat algorithmic bias.

She delivers a reality check on faculty adoption: throwing grant money at professors will not yield lasting integration unless institutional structures formally reward AI scholarship in tenure and promotion guidelines. Without structural credit, AI initiatives will end up abandoned like obsolete Betamax tapes. Furthermore, Dr. Melton stresses the non-negotiable need for close institutional alignment with IT departments. Describing her collaborative relationship with campus IT, she shares an incident where an AI tool went rogue on their campus network, and because of deep operational coordination, the IT team was able to isolate and neutralize the tool within 8 minutes.

- **Mitigating algorithmic bias**: Active engagement with model developers and crowd-sourced reinforcement learning (thumbs up / thumbs down). - **Faculty incentives**: AI integration must be formally recognized in tenure, promotion, and scholarship criteria to prevent tool abandonment. - **IT response capability**: Close alignment between academic leadership and IT enabled a rogue campus AI tool to be shut down in 8 minutes.

---

[14:42](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=882s) The Playbook for Action and AI "Snitchers"

In her closing remarks, Dr. Melton reiterates that high-level policy frameworks are meaningless without an actionable implementation playbook connecting faculty, students, and IT infrastructure. She urges institutions to move past outdated assumptions—symbolized by the red-and-white yield sign—and commit to active, practical AI integration.

She concludes with an anecdote about recovering from a broken ankle while wearing AI-enabled smart shoes. After promising her physical therapist that she would complete her daily rehabilitation exercises, the embedded sensors tracked her actual movement and transmitted the data directly to her medical provider, exposing that she had skipped her routine. Drawing a final laugh from the room, Dr. Melton quips that the shoes are no longer called "sneakers" but "snitchers," leaving the audience with an inspiring, grounded vision of "AI in action."

## Notable quotes > [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) convincing higher education faculty to embrace new technology — Dr. Robbie Melton

> [02:56](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=176s) settle people down — Dr. Robbie Melton

> [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) AI in Action — Dr. Robbie Melton

> [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) AI gurus — Dr. Robbie Melton

> [09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) Starship Enterprise — Dr. Robbie Melton

> [09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) on point — Dr. Robbie Melton

> [14:42](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=882s) snitchers — Dr. Robbie Melton

## Mentioned Dr. Robbie Melton, Tennessee State University (TSU), NASA, Candy Crush, ChatGPT 3.5, Google Gemini, Napkin AI, TikTok, Kickstarter, Betamax, Starship Enterprise, The Flintstones

## Video description Robbie Melton, Vice President of SMART AI for ALL Applied Research & Innovations, Tennessee State University-SMART AI for ALL Applied Research Center

How can higher education institutions transform AI policy from compliance requirement into strategic opportunity for equity and excellence?

I will present research examining comprehensive AI policy implementation at a university serving underrepresented populations, revealing how thoughtful policy frameworks can simultaneously advance innovation, protect academic integrity, and promote equitable access to emerging technologies. The talk will illustrate how our institution navigated the complex challenges of becoming both policy implementer and research entity, providing practical insights into what actually works when introducing transformative technology across diverse stakeholder groups.

I will share findings from quantitative policy compliance analysis and qualitative stakeholder assessments that demonstrate successful AI integration demands far more than technical guidelines. The presentation will show how we developed comprehensive professional development programs, transparent communication channels, and adaptive governance structures that respond to rapidly evolving AI capabilities while maintaining academic standards. I will explain specific strategies for stakeholder engagement, phased implementation approaches, and assessment methodologies that balance innovation with accountability.

Attendees will learn actionable frameworks for navigating the tensions between embracing AI innovation and preserving educational excellence, with particular emphasis on how institutions can model ethical integration prioritizing accessibility, cultural responsiveness, and social equity. I will demonstrate how policy frameworks can empower rather than restrict institutional communities, transforming compliance challenges into opportunities for institutional distinction and student preparation for AI augmented professional environments.

Join this session to discover evidence based strategies for positioning your institution at the forefront of responsible AI integration while leading national conversations about technology democratization in education.

[Source](https://www.youtube.com/watch?v=oWVYCJ3ICTY)

中文简报

田纳西州立大学废除AI禁令，将终身教职与技术应用挂钩高校禁令之所以失效，是因为技术演进速度超过了官僚政策的制定，这要求院校重新设计课程体系，并在终身教职评审中认可AI学术成果以确保技术应用。 Robbie Melton 博士探讨了学术界反复出现的技术焦虑周期，呼吁高校摒弃被动出台的禁令，转而采用动态演进的“行动中的AI”（AI in Action）现行政策。结合田纳西州立大学的推行经验，她主张应当重新设计作业而非一味审查软件，并强调滥用AI反映的是教学设计的滞后。Melton 博士通过可穿戴技术以及源自 TikTok 等平台的消费级工具展示了丰富教育路径的实际应用。为实现可持续的机构化采纳，她强调必须通过终身教职和职称晋升认可来激励教师，同时与IT基础设施部门保持紧密的协同合作。 Robbie Melton 指出，高校面对生成式 AI 时采取的行政封禁做法重蹈了过去抵制手机的覆辙，忽视了现代设备远超当年阿波罗登月系统的巨大算力潜能。 (2:56) 田纳西州立大学（TSU）历时一年制定的政策在获批时已显滞后，促使学校转向建立包容行政与采购人员的动态“行动中的 AI”（AI in Action）框架，并提倡重构教学考核而非一味惩罚作弊。 (5:03) AI 技术不仅限于桌面文本生成，更扩展到防侵害化学检测指甲油等可穿戴设备；TSU 追踪测试 TikTok 涌现的消费级工具，发现其教育应用适用率高达 82%。 (9:30) 高校若要真正推动教师拥抱 AI，必须将其正式纳入终身教职（Tenure）与晋升考评体系，同时保持与 IT 部门的紧密协同以确保在数分钟内处置安全隐患。 (11:48)

Reading summary

Dr. Robbie Melton argues that higher education must move past reflexive bans and outdated mental models by adopting dynamic institutional policies, authentic pedagogical redesign, structural faculty incentives, and close IT alignment. Overcoming Outdated Mental Models and Reflexive Bans (0:04) Dr. Melton illustrates academia's persistent resistance to technological shifts through a yield sign demonstration: audiences consistently identify yield signs as yellow, even though they have been red and white for over 45 years. She contends that university administrators exhibit a similar lag when encountering generative artificial intelligence, echoing historical panics surrounding the introduction of campus internet access, mobile phones, and Massive Open Online Courses (MOOCs). To contextualize modern hardware capabilities, Dr. Melton points out that contemporary smartphones possess far more computing power than the NASA systems that supported the Apollo moon landings, yet society largely directs this capability toward casual games like Candy Crush. She argues that when institutions do not understand a technology's operation or pedagogical value, their default administrative reflex is to institute bans rather than examining how to integrate the tools productively. Living Institutional Policy and Pedagogical Reform (5:03) Reflecting on Tennessee State University's (TSU) governance initiatives, Dr. Melton notes that drafting an institutional AI policy required an entire year of campus deliberation. By the time the governing board formally approved the document, the underlying technology had already evolved past it. This delay prompted TSU to establish "AI in Action," an open-ended, adaptive framework that actively engages previously overlooked institutional participants, including administrative staff, procurement officers, and local community members. Addressing academic integrity concerns, Dr. Melton rejects the premise that artificial intelligence created student cheating, remarking that students have found workarounds across every technological era. In her view, if an assignment can be completed effortlessly by an AI model, the instructor's pedagogical design is fundamentally obsolete. She asserts that educators must redesign coursework to emphasize critical thinking and authentic assessment rather than relying on punitive surveillance software. Sourcing and Evaluating Emerging Consumer Technologies (7:18) Because formal AI instruction remains limited across higher education, Dr. Melton observes that most students and faculty are self-taught using free tiers of foundational tools. To ground artificial intelligence in tangible applications, she personally tests emerging consumer devices, including AI-enabled smart glasses, chemical-sensing nail polish designed to detect date-rape drugs in drinks, and sensor-equipped rehabilitation shoes that log physical therapy compliance. To track the rapid pace of technological change, TSU actively monitors consumer hardware and software releases featured on TikTok. The university formed a specialized review committee tasked with purchasing and testing these emerging tools for instructional viability. Dr. Melton reports that over 82% of the consumer technologies evaluated through this process proved effective for integration into teacher education and university degree pathways. Structural Faculty Recognition and Network Safeguards (11:48) Dr. Melton warns that short-term grant funding will not produce sustained technology adoption unless universities formally incorporate AI scholarship and integration into tenure and promotion criteria. Without these structural incentives, she predicts faculty will eventually abandon institutional AI initiatives once initial enthusiasm wanes. In addition, Dr. Melton emphasizes the necessity of direct engagement with technology developers to address algorithmic bias and underrepresentation of marginalized populations in foundation models, urging users to submit active reinforcement feedback. Operationally, she underscores that academic leaders must partner closely with campus IT personnel, noting that this operational alignment enabled TSU's network administrators to isolate and neutralize an unauthorized campus AI tool within eight minutes. Dr. Melton concludes that high-level policy declarations remain ineffective without an operational playbook linking pedagogy, community stakeholders, and technical infrastructure. Sustainable adoption ultimately depends on an institution's willingness to reform faculty tenure evaluations and maintain real-time IT safeguards alongside educational experimentation.

精炼阅读摘要

Dr. Robbie Melton指出，高等教育机构面对人工智能的冲击，不应重蹈因认知滞后而简单下达禁令的历史覆辙，而应摆脱陈旧心智模式，构建包容多方利益群体的动态“行动中AI”（AI in Action）政策，并通过彻底重构课业设计、将AI成果纳入终身教职评审机制，以及深化与IT部门的安全协同，实现全方位的组织变革。打破认知惯性与全面禁用的管理反射 (2:56) Dr. Robbie Melton强调，高等教育界对新技术的阻抗源自根深蒂固的人类认知惯性。正如公众普遍误以为让行标志（yield sign）依然是黄色（实际上变更为红白双色已超过45年），许多教职人员面对AI时仍固守过时的教学与评估模型。回顾以往学界对慕课（MOOCs）、万物互联以及手机进入课堂所引发的剧烈争议，高校管理者面对无法理解的技术运作机制与潜力时，下意识的行政反射往往是一概禁止。 Melton将现代硬件的飞跃置于历史维度中对比：当下普通智能手机的计算能力远超当年NASA将人类送上月球所使用的计算系统，但大众主要用其运行带来超过10亿美元收入的休闲游戏《糖果传奇》（Candy Crush）。如果高校因为缺乏理解而对生成式AI实施惩罚性封禁，便等于重演历史盲动，白白错失利用高算力推动教学变革的核心机遇。构建动态行动政策与重塑评估机制 (5:03) 田纳西州立大学（TSU）在推进AI政策制定的过程中遭遇了严峻挑战，因校内各派意见不一，整整耗费了一年时间才获得校董会批准，而此时底层AI技术早已发生了颠覆性迭代。这一教训表明，高校制定静态、封闭的技术政策注定面临发布即过时的困境。TSU据此提出了“行动中的AI”（AI in Action）框架，主张建立开放式、持续适应的动态规范，并将此前常被忽视的行政人员、采购部门和本地社区伙伴等利益相关者全面纳入治理架构。针对席卷学界的学术诚信恐慌，Melton指出学生寻求作弊捷径的现象自古有之，并非大语言模型带来的全新产物。她直言，如果现有的课程作业能够被学生轻而易举地利用AI全盘代劳，其根本问题在于教师的教学与评估设计本身存在结构性缺陷。作为终身正教授，她明确主张教师不应沦为技术的监管警察，而应在伦理与法律边界内善用AI，通过重塑课业设计来培养学生真实的批判性思维与高阶能力。探索穿戴式硬件与社交媒体技术筛查 (7:18) 针对多数高校师生主要依赖免费的ChatGPT 3.5且缺乏系统性指导的现状，Melton主张高等教育必须将视线扩展至桌面文本生成工具之外，进入更为广阔的人性化实用场景。她展示了亲自测试的AI智能眼镜，以及用于检测饮料中迷奸药物成分的化学感应指甲油，以此论证AI已融入可穿戴设备与人身安全防护之中。她呼吁学术界不应仅停留在对数据中心环境足迹与技术滥用的宏观忧虑上，更应聚焦于能够切实提升科研深度、学生身心健康和课堂生产力的实证应用。为了紧跟Google Gemini每日更新以及Napkin AI等自动化幻灯片工具快速迭代的节奏，TSU采取了一项极具开创性的机制：将TikTok视作新时代的Kickstarter平台，设立专门的审查委员会追踪并采购社交媒体上涌现的新兴消费级AI产品。测试数据显示，委员会审查的消费级工具中有超过82%被证实切实可行，能够有效转化为正式学位培养路径和教师教育方案的教学组件，践行了主动拥抱年轻群体技术生态的策略。纠正算法偏见与构建机制化保障支撑 (11:48) 在AI伦理与公平性层面，Melton回顾了自己在两年半前直接联络主流AI模型开发者的经历，针对算法提示词在图像与文本生成中对弱势群体的严重代表性偏见发起挑战。科技企业积极回应了这类反馈，她因而敦促高校使用者坚持利用系统内置的点赞和点踩等强化学习机制，主动训练并纠偏算法模型，以在技术底层阻断偏见扩散。在组织机制方面，Melton提出单靠项目经费补助无法在教师群体中实现长久的技术融合；大学必须在终身教职（Tenure）与职称晋升评定体系中正式承认AI学术成果与教学创新，否则各类试点项目终将如同被淘汰的Betamax录像带一样归于沉寂。与此同时，学术管理层必须与校园IT部门形成高度协同。TSU的一次实战案例印证了这种深层合作的威力：当校内网络中出现一款违规失控的恶意AI工具时，学术部门与IT团队的高效响应机制使其在短短8分钟内便被成功隔离并清除威胁。 Melton总结强调，若缺乏连接教师、学生与技术底层架构的实操落地指南，任何宏观政策框架都将沦为空谈；高校必须跨越如同黄色让行标志一般的认知盲区，以务实态度迎接变革。正如她借由能向物理治疗师实时回传康复运动数据的“告密智能鞋”（snitchers）所隐喻的，AI深度融入教育与生活已是定局，但高校在面对技术黑盒、数据隐私保护以及长期制度适配力方面，仍需经受深层次的机制考验。

Detailed notes — zh

## Background 本视频由 Ai4 于 2026 年 8 月 14 日发布在 YouTube 平台。视频记录了田纳西州立大学 SMART AI for ALL 应用研究中心副校长 Robbie Melton 的主题演讲，介绍如何将高等教育中的 AI 政策从被动的合规要求转化为推动教育公平与学术卓越的战略契机，并分享了该校在全流程 AI 治理与组织变革中的实践经验。 ## TL;DR 演讲者通过“让行标志颜色测试”揭示了教育工作者面对新技术时的认知惯性，强调不应因恐惧作弊而封杀 AI，而应倒逼教学考评机制的重构。田纳西州立大学构建了全员参与、动态演进的“行动中的 AI”政策，甚至通过 TikTok 等新兴平台采购前沿工具并取得了超 82% 的教学契合度。Melton 呼吁高校主动介入算法偏见纠偏，并将 AI 教学科研成果与教师终身教职（Tenure）晋升直接挂钩以提供实质激励。结合智能防下药指甲油、康复“告密鞋”以及与 IT 部门 8 分钟关停失控工具等生动案例，演讲展示了一套平衡创新、安全与实效的 AI 落地路线图。 ## Atmosphere & style 演讲现场氛围极其热烈且充满笑声，Melton 以脱口秀般极具感染力和幽默感的台风打破了学术政策报告的沉闷刻板。她巧妙地在硬核的高校治理议题与防下药指甲油、“会告密的鞋子”等鲜活具象的生活案例之间自如切换，互动感极强。整场分享既有资深教授直面技术浪潮的豁达与前瞻，又充满了务实干练的实操智慧，让听众在阵阵欢笑中深受启发。 ## Key takeaways - [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) 高等教育面对新技术的本能反应往往受制于认知惯性，需要打破“旧经验适用新现实”的思维定势以包容心态接纳 AI。 - [02:44](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=164s) 大众与教育界常因缺乏驾驭颠覆性算力的能力而习惯性诉诸禁令，高校应警惕因恐惧而封杀 AI 的被动防御心理。 - [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) 静态的高校政策在 AI 飞速迭代面前极易失效，必须制定面向教师、学生、行政与采购等全利益相关者的动态开放式“行动中的 AI”框架。 - [05:45](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=345s) 作弊并非 AI 催生的新产物；如果学生能轻易使用 AI 作弊通过考核，说明教师的教学设计与评价机制亟需重构升级。 - [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) 公众对 AI 的恐惧可通过具象化、实用化的生活场景来化解，例如展示防下药智能指甲油、智能眼镜等提升安全健康的落地应用。 - [07:50](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=470s) 普遍认知往往停留在免费版对话工具的自学摸索阶段，高校亟需建立从起点到终点、基于实证数据的系统化 AI 落地框架。 - [09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) 通过建立前沿技术敏捷采购机制（如挖掘社交平台前沿产品），可实现新兴工具与专业培养方案超 82% 的高匹配转化率。 - [10:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=630s) 教育工作者与弱势群体应积极利用日常交互反馈机制（如点赞/点踩）主动纠偏，推动科技厂商消除算法中的潜在偏见。 - [12:53](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=773s) 教师专业发展不能仅停留在经费补贴层面，必须将 AI 教学与研究成果正式纳入终身教职（Tenure）评审等学术考评核心机制。 - [13:35](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=815s) 推行 AI 创新必须与 IT 部门建立紧密协同防线，确保对失控或异常工具能够在数分钟内实现快速隔离与安全管控。 ## Detailed walkthrough ### [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) 科技变革的循环与思维定势：让行标志的颜色测试 Robbie Melton 登台后直言不讳地指出，自己在高等教育领域承担着“全世界最艰难的工作”——帮助高校教职员工接纳新技术。她特别强调自己说的是广义的“技术”而不仅仅是当前的“AI”。作为一名经历过互联网进入高校前时代的资深学者，Melton 回顾了过往历史中每一次技术浪潮掀起的恐慌与抵触，无论是当年的“万物互联”（Internet of Everything）还是后来引发“在线教学怎么可能学到东西”质疑的慕课（MOOCs），如今围绕 AI 的争议与当年的情形如出一辙。为了证明人们是如何下意识地受制于过时认知，Melton 现场发起了一个互动小测试，让全场观众不加思索地大声喊出“让行标志（Yield Sign）是什么颜色”。当全场不约而同地喊出“黄色”时，Melton 笑着揭示了真相：让行标志早在 45 年前就已改成红白相间，黄色早已成为历史。这个生动的例子直指人类认知惯性的核心：人们常常牢固地坚守着早已发生改变的旧知识，因此面对新技术的冲击，大家最需要的是打破认知惯性、相互支持。 ```mermaid flowchart TD accTitle: 认知惯性与技术变革对比流程 subgraph S1["认知惯性示例：让行标志"] A["直觉认知（过时经验）<br/>'让行标志是黄色的'"] --> B["客观现实（技术/规则演进）<br/>45年前已更新为红白相间"] end subgraph S2["高等教育技术转型演进"] C["前互联网/打孔机时代"] --> D["万物互联与 MOOCs 争议"] D --> E["生成式 AI 浪潮与全面赋能"] end ``` ### [02:44](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=164s) 算力跃升与现实反差：从登月级算力到禁止工具 Melton 将自己在全球 AI 转型浪潮中的角色定位为“让大家冷静下来的人”。她掏出智能手机指出，仅仅在 20 年前，教育界还在激烈辩论“校园里到底应不应该允许智能手机存在”，甚至至今各地仍有人固执地使用带天线的旧手机。技术的推进总会伴随着一部分人的抗拒与另一部分人的探索。智能手机的计算能力早已远远超过当年人类阿波罗登月时所使用的计算机总和，但绝大多数人日常最主要的使用方式却是玩《消消乐》（Candy Crush）这类累计营收超 10 亿美元的手游。面对功能如此强大的工具，人们往往由于不知如何有效利用，第一反应就是“全面禁止”。对待 AI 也是同样的心理防御机制，高等教育若因恐惧而选择封杀，无异于重蹈覆辙。 - **登月级算力 vs. 休闲娱乐**：智能手机拥有超越登月计算机的算力，大众却主要将其用于创造十亿美元产值的手机游戏。 - **应对未知的习惯性反应**：当教育体系不知道如何驾驭一项颠覆性工具时，往往会诉诸禁令。 ### [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) 田纳西州立大学的“行动中的 AI”政策与作弊争论田纳西州立大学（TSU）在制定 AI 政策时经历了一整年的拉锯战，各方争执不下；然而当校董会最终批准该政策时，由于技术迭代飞快，政策本身几乎已经过时。Melton 强调，当今时代的政策框架必须具备开放性（Open-ended）与动态适应性，并且要广泛涵盖所有利益相关者——除了教师和学生外，还要将以往常被遗漏的行政人员、采购部门乃至整个社区纳入其中。田纳西州立大学据此打造了名为“行动中的 AI”（AI in Action）的活态政策。针对教育界对“学生会用 AI 作弊”的最大担忧，Melton 展现了极其豁达和前瞻的教学观。她幽默地表示，早在石器时代（Flintstones）打孔机写论文的年代就有人作弊，作弊并非 AI 带来的新产物。作为终身正教授，她的教学态度十分明确：“如果你打算用 AI，尽管去‘作弊’。因为如果我的教学方式能让你轻易通过 AI 作弊蒙混过关，那是我作为授课教师的教学出了问题。”在合规、合法与合乎伦理的前提下，AI 应当成为提升教学质量的有力杠杆。 ```mermaid flowchart LR accTitle: 行动中的 AI 政策构建要素 subgraph G1["全方位利益相关者"] A["教职员工 & 学生"] B["行政 & 采购部门"] C["外部社区群体"] end subgraph G2["政策核心理念"] D["开放性与活态演进<br/>(AI in Action)"] E["重构教学考评机制<br/>(防止被动防作弊)"] end G1 --> D D --> E ``` ### [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) 落地可感的 AI：从防下药指甲油到全流程实施框架当前大众对 AI 的认知往往局限在“ChatGPT 3.5 免费版”，而且大部分用户的技能属于未经专业培训的自学摸索。Melton 强调，即便自诩为 AI 专家，在飞速演进的当下也必须持续学习。公众对 AI 的恐惧大多聚焦在数据中心能耗、环境影响与滥用风险上，化解恐慌的最佳途径是让技术以具象化、实用化的形式融入生活。 Melton 现场展示了她佩戴的 AI 智能眼镜以及涂抹的“智能 AI 指甲油”——这种特制指甲油能够在接触到约会强奸药物时发生反应并预警。当人们看到技术能够切实保护人身安全、提升健康与生活质量时，对技术的抗拒就会转为接纳。高等教育需要建立起一套从起点到终点的全流程实施框架，以实证数据来证明 AI 能够全面赋能教学、学习、学术研究与生产力提升。面对像 Gemini 升级或 Napkin AI 自动生成幻灯片这类日新月异的技术，整个教育界正如同航行在未知领域的“企业号星舰”（Starship Enterprise）。 - **AI 普及的断层**：普遍认知停留在免费版大语言模型，缺乏系统化培训与实证支持。 - **具身与可穿戴 AI 示例**：防下药检测智能指甲油、AI 智能眼镜展示了技术在安全与健康层面的实际落地应用。 ### [09:30](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=570s) 拥抱前沿与消除偏见：TikTok 采购审核与算法反馈机制为了打破传统教育转型的滞后性，田纳西州立大学甚至设立了专门的采购与审核委员会，直接从 TikTok 等新兴社交平台上挖掘并采购最新前沿科技产品。这一举措最初引来不少疑惑与笑声，但实证评估表明，通过该机制筛选并融入教育学位路径的技术工具，其实际应用精准度（On point）高达 82% 以上。在算法公平性方面，Melton 分享了她早在两年半前就主动介入算法偏见治理的经历：当时大模型生成的提示词结果对弱势群体（Underrepresented groups）存在严重失真与偏见，她直接向各大 AI 厂商致电交涉。令她欣慰的是，各大科技公司迅速给予了积极回应并建立了反馈渠道。Melton 呼吁在场的所有教育工作者积极使用界面中的“点赞”（Thumbs up）和“点踩”（Thumbs down）按钮，因为每一次微小的反馈都在实质性地参与模型纠偏与消除潜在偏见。 - **TikTok 科技转化率**：经过专门委员会审核与采购的新兴技术，与教育专业培养方案的契合有效度超过 82%。 - **算法反偏见介入**：主动向 AI 厂商反馈弱势群体表征缺陷，利用底层交互反馈通道推动模型伦理修正。 ### [12:53](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=773s) 教师激励、IT 协同机制与“会告状的鞋” 对于高校推行教师专业发展（Professional Development），Melton 指出单纯提供经费补贴毫无意义。如果 AI 相关的教学与研究无法被正式纳入学术成果考评、无法与终身教职（Tenure）晋升评定直接挂钩，这项技术最终就会像当年被淘汰的 Betamax 录像带一样沦为弃儿。为此，她提供了一套涵盖教师、学生和 IT 技术部门协同作战的行动指南（Actionable Playbook）。 Melton 用“我和 IT 部门谈恋爱”这句幽默的话强调了技术支持团队的关键地位——IT 掌控着软硬件准入的大门。她分享了一个真实案例：学校曾遭遇一个“失控走偏”（Went rogue）的 AI 工具，正是在 IT 部门的紧密协同下，团队在短短 8 分钟内就成功将其隔离并关停。演讲最后，Melton 提到了自己脚上穿的智能鞋：因为自己曾摔断过脚踝并向医生保证会每天康复锻炼，这双智能鞋只要监测到她偷懒没锻炼，就会自动给理疗师打电话打小报告，因此它们不再是“运动鞋”（Sneakers），而是变成了“告密鞋”（Snitchers）。她借这番欢声笑语再次总结，AI 时代已经不可逆转地到来，高校必须建立起真正富有实效的“行动中的 AI”生态。 - **教师激励机制核心**：必须将 AI 融入学术考评体系，作为晋升终身教职的硬性评价指标。 - **安全响应速度**：建立紧密的 IT 协同防线，在 8 分钟内成功处置异常失控的 AI 工具。 - **生活化智能硬件**：将运动鞋转变为监测康复训练合规性的智能终端（Sneakers $\rightarrow$ Snitchers）。 ## Notable quotes > [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) 在高等教育领域承担着‘全世界最艰难的工作’——帮助高校教职员工接纳新技术。 — Robbie Melton > [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) 让行标志是什么颜色 — Robbie Melton > [00:04](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=4s) 让行标志早在 45 年前就已改成红白相间，黄色早已成为历史。 — Robbie Melton > [02:44](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=164s) 让大家冷静下来的人 — Robbie Melton > [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) 行动中的 AI — Robbie Melton > [05:03](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=303s) 如果你打算用 AI，尽管去‘作弊’。因为如果我的教学方式能让你轻易通过 AI 作弊蒙混过关，那是我作为授课教师的教学出了问题。 — Robbie Melton > [07:18](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=438s) 企业号星舰 — Robbie Melton > [12:53](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=773s) 我和 IT 部门谈恋爱 — Robbie Melton > [12:53](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=773s) 如果 AI 相关的教学与研究无法被正式纳入学术成果考评、无法与终身教职晋升评定直接挂钩，这项技术最终就会像当年被淘汰的 Betamax 录像带一样沦为弃儿。 — Robbie Melton > [12:53](https://www.youtube.com/watch?v=oWVYCJ3ICTY&t=773s) 它们不再是‘运动鞋’，而是变成了‘告密鞋’。 — Robbie Melton ## Mentioned Robbie Melton, Tennessee State University (田纳西州立大学), ChatGPT 3.5, Gemini, Napkin AI, TikTok, Candy Crush (消消乐), Betamax, Starship Enterprise (企业号星舰), Flintstones (摩登原始人) ## Video description Robbie Melton, Vice President of SMART AI for ALL Applied Research & Innovations, Tennessee State University-SMART AI for ALL Applied Research Center How can higher education institutions transform AI policy from compliance requirement into strategic opportunity for equity and excellence? I will present research examining comprehensive AI policy implementation at a university serving underrepresented populations, revealing how thoughtful policy frameworks can simultaneously advance innovation, protect academic integrity, and promote equitable access to emerging technologies. The talk will illustrate how our institution navigated the complex challenges of becoming both policy implementer and research entity, providing practical insights into what actually works when introducing transformative technology across diverse stakeholder groups. I will share findings from quantitative policy compliance analysis and qualitative stakeholder assessments that demonstrate successful AI integration demands far more than technical guidelines. The presentation will show how we developed comprehensive professional development programs, transparent communication channels, and adaptive governance structures that respond to rapidly evolving AI capabilities while maintaining academic standards. I will explain specific strategies for stakeholder engagement, phased implementation approaches, and assessment methodologies that balance innovation with accountability. Attendees will learn actionable frameworks for navigating the tensions between embracing AI innovation and preserving educational excellence, with particular emphasis on how institutions can model ethical integration prioritizing accessibility, cultural responsiveness, and social equity. I will demonstrate how policy frameworks can empower rather than restrict institutional communities, transforming compliance challenges into opportunities for institutional distinction and student preparation for AI augmented professional environments. Join this session to discover evidence based strategies for positioning your institution at the forefront of responsible AI integration while leading national conversations about technology democratization in education. [Source](https://www.youtube.com/watch?v=oWVYCJ3ICTY)

Source quotes

[0:04] Robbie Melton: 在高等教育领域承担着‘全世界最艰难的工作’——帮助高校教职员工接纳新技术。 [0:04] Robbie Melton: 让行标志是什么颜色 [0:04] Robbie Melton: 让行标志早在 45 年前就已改成红白相间，黄色早已成为历史。 [2:44] Robbie Melton: 让大家冷静下来的人 [5:03] Robbie Melton: 行动中的 AI [5:03] Robbie Melton: 如果你打算用 AI，尽管去‘作弊’。因为如果我的教学方式能让你轻易通过 AI 作弊蒙混过关，那是我作为授课教师的教学出了问题。 [7:18] Robbie Melton: 企业号星舰 [12:53] Robbie Melton: 我和 IT 部门谈恋爱 [12:53] Robbie Melton: 如果 AI 相关的教学与研究无法被正式纳入学术成果考评、无法与终身教职晋升评定直接挂钩，这项技术最终就会像当年被淘汰的 Betamax 录像带一样沦为弃儿。 [12:53] Robbie Melton: 它们不再是‘运动鞋’，而是变成了‘告密鞋’。

Source quotes

[0:04] Dr. Robbie Melton: convincing higher education faculty to embrace new technology [2:56] Dr. Robbie Melton: settle people down [5:03] Dr. Robbie Melton: AI in Action [7:18] Dr. Robbie Melton: AI gurus [9:30] Dr. Robbie Melton: Starship Enterprise [9:30] Dr. Robbie Melton: on point [14:42] Dr. Robbie Melton: snitchers

Original transcript

[0:04] My name is Robbie Melton. I come to you from many schools, many lands, and again, I'm hoping that [0:13] by you being here, you already know about AI. I have the hardest job in the world, [0:22] and that is to help faculty in higher education to embrace technology. You didn't hear me say AI. [0:34] I said technology. So, when I look around the room, I can say to some of you, I am the oldest [0:44] one here. I am before the internet that hit higher ed, and the same issues, problems, concerns as AI, [0:57] here I am again. So, I am your game-changer. I'm the person that can come in to your institution [1:08] and let them shoot me. I have been around. Some of you might remember internet of everything. [1:18] You remember how we just went, "Oh my gosh!" And don't forget MOOCs. "Oh, how in the world can you [1:24] learn online?" So, with that, I have all of the old paradigms, the new paradigm, but I'm here to [1:33] prove to you why we need each other. I'm going to ask you, yes, to use your phones. That's not new, [1:43] but now we ban phones. So, I'm going to ask you a very simple question. Right now, I don't want you [1:50] to think about it. I just need for you to yell out. Are you ready? What color is a yield sign? [2:00] Okay. I'm done. I'm good. Now you know why we need each other. The yield sign has not been [2:07] yellow in 45 years. It is red and white. Why do I use this all the time? Because we all hold on [2:20] to knowledge that has changed. And sometimes it's automatic. [2:27] And many of you right now is holding that phone. Let me check to see in Las Vegas [2:35] if there has been a change. Yes, they have. And if you're from Canada, yes, it's red and white. [2:44] Ladies and gentlemen, my job, as we go through the AI transformation, is to settle people down. [2:56] There's the when, the why, and the how. And again, I have to go all over the globe to let people know [3:04] life is good. So, with all of the AI engines, I want you all to see what I'm holding in my hand. [3:15] And it's only 20 years ago when we had the big debate about should we even have smartphones? [3:26] And there's always somebody, wherever I go, that still has a phone with an antenna. [3:34] They refuse. You got to understand, there are those people who will move on and those people [3:42] who, like you, need to know what are the advantages and the disadvantages. [3:49] Everyone with this phone, I'm going to give you a little information. Here we have in our hands one [3:57] of the most powerful pieces of technology called the smartphone. It is so powerful that it has more [4:10] technology computational technology than what we put the man on the moon. Ladies and gentlemen, [4:20] I'm here to share with you and you can check it, you can Google it. [4:26] What do we do with this phone, ladies and gentlemen? We play Candy Crush. Now, here's [4:33] where you all wake up and now I'll get to the AI policy. Candy Crush grossed over $1 billion. [4:47] We have in our hands an amazing tool and as George said, the previous speaker, [4:56] we don't even know how to use it. So, what do we do? When we don't know, we ban it. [5:03] And that's where we are with AI. We have an AI policy. Look, it took a whole year to develop. [5:12] Why? No one could agree. And guess what? As soon as our board approved it, it was almost outdated. [5:23] Please know that now in this day and time, if you're going to have a policy, [5:29] you have to have it open-ended and it has to represent all of your stakeholders. Of course, [5:36] we had faculty. Of course, we had students. But guess who we missed out on? The administrators, [5:43] procurement. How about our community? So, with that, on behalf of Tennessee State University, [5:51] we develop a policy that we wanted it to be livable. We call it AI [6:01] in action. So, with that, we wanted to make sure that we address all of the concerns. So, [6:09] everyone here's the number one concern that we all know. People will cheat with it. Look at me. [6:20] Really? Do you know, as I shared, I'm before the internet. I had to create my dissertation [6:30] on a key punch machine, and guess what? Even with the Flintstones, they were cheating. Ladies and [6:36] gentlemen, we have to get beyond that, and so I say, yes, I teach. If you're going to use AI, [6:45] feel free to cheat. Because if I'm teaching the same way where you can cheat with AI, then [6:54] something is wrong with me as an instructor. I'm a full professor, tenure, and I've been around. [7:01] I have to understand that this piece of technology used legally, appropriately, [7:08] ethically, can enhance teaching and learning if we only know the training. So, with that model, [7:18] I want to share with you the awareness. Everybody knows AI, and all you have to [7:25] hear is Chat GPT 3.5 free. Did you hear that free at the end? And then when you ask them, [7:33] as George indicated, by the way, I just met George, who trained you? Usually it's self-taught. [7:44] Ladies and gentlemen, we are here at a major national conference. You have to learn something [7:51] new about AI, even if you are the AI guru of your world. This piece of technology is changing and [8:01] as you see from the slides, we know the policy. We know the ins and out, but if I ask all of you [8:10] right now, do you know in your hand you already have AI? Ladies and gentlemen, I usually wear AI. [8:19] Today I have my AI glasses and I have my smart AI nail polish. See, now you're going to look up [8:28] cuz you're going to say, "What did she say?" Oh, yes. My nail polish are coded for date-rape drugs. [8:37] See, when you start bringing technology down to the level where people can appreciate it, [8:44] then life is good. Because again, we hear all of the dangers of AI and yes, there are dangers, [8:53] data center, the environment and using it inappropriately. But I want a conference where [9:01] someone can share with me with evidence the use of AI that will enhance teaching, learning, research [9:11] and productivity and our health. So, what I have for you is our full framework starting from the [9:19] beginning to the end. But it's only a framework, everyone, as well as where we need to go. And [9:30] where is that? We're like the Starship Enterprise. We don't know yet because even this afternoon, [9:39] if you are using the AI tool of Gemini, there was a major upgrade. If you're using napkin AI, [9:52] let me share with you. I'm a happy camper because now you can do slides. I [10:00] evaluate AI up and down. I wear AI. Interesting, if you are a TikTok and watch this everyone, [10:11] and we know that it was banned, but all of us are on TikTok. [10:16] Anyone remember Kickstarter? Anyone in here? Yes. Well, guess what? You will find more technology [10:25] on TikTok than the line dancing. Not only that, on behalf of helping people to adopt [10:36] AI, especially our students, we purchase all of the technology from TikTok. You all didn't laugh? [10:46] And interesting, we have a committee to vet that technology, and I'm here to say the technology [10:54] that we have purchased to help people who are looking at it, using, and to help it to pathway [11:02] into our education degrees have been up over 82% on point. Did you all hear that? On point. [11:12] You can ask me, and I can let you know. That's where the student dilemma come in, because again, [11:20] our students are using AI, our faculty, but again, the policy allows them the freedom, [11:29] but until we have people like you to help us with the evidence. So again, I have all of the [11:37] information in terms of our smart research center, but what you really need is how we are using AI. [11:48] So from data to again bridging the hidden biases. I'm the person who called in two and [11:57] a half years ago to say underrepresented groups are not looking good when you prompt into AI. [12:08] And I'm pleased to share with you all the companies responded back in a positive manner. [12:17] So I I don't know about you am able to say thank you because they did call us and said give us [12:26] feedback. So I say to you, when you see something when you use AI, you'll always see that thumb up [12:36] or that thumb down. How many of us help shape this model by just clicking thumbs up and thumbs down? [12:47] That's one way where you can start to become involved and address the biases. [12:53] So what I have for you is the professional development chart. Ladies and gentlemen, [13:00] you can throw all of the money you want to your faculty to say use AI. Until you are able to help [13:09] them to embrace AI where it is scholarship, it counts for tenure, promotion, and they can use it [13:19] freely, then it will be like the Betamax machine that I still have where you all went to the other [13:27] platform, VCR. So, wrapping up, I have for you all of the framework that you need. But, again, [13:37] framework without action means it's just that. I have for you an actionable playbook in working [13:47] with your institution, your faculty, students, and your technology services. Ladies and gentlemen, [13:55] I want you to know I date my IT department. Why? Because they have the key to the door to let [14:05] things in or out. If you are from IT, I thank you very much. We had an AI tool that went rogue on [14:15] us. And again, working with our IT, we were able to kill it within 8 minutes. 8 minutes. [14:28] These things are there, but we cannot ban them. So, I have for you the playbook. [14:36] I have for you all of the information, but what I want to leave you with [14:42] as we conclude this part, you all now know the color of a yield sign. [14:51] You all know that you have to have AI in action. The fact that I can come to you [14:58] with smart nail polish, Chanel, mhm. I wish you could have seen where I had my AI shoes. AI shoes? [15:09] Yes, ladies and gentlemen. So, that when I am to work out because I happened to break an ankle, [15:17] and of course I said I would work out every day. My smart shoes will call my therapist [15:25] to say, "No, she did not." That's why they're no longer called sneakers, but snitchers. [15:33] I want to thank you all very much. Again, I hope you've had a chance to laugh and smile about AI. [15:42] It is here, and if you ever see me, just ask me what is AI in action. Thank you all very much.