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    <title>Co-Intelligence Living and Working with AI</title>
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    <description>This podcast features in-depth conversations between two hosts exploring the evolving role of artificial intelligence in knowledge work and higher education. Each episode examines how AI is reshaping professional practices, learning environments, and human collaboration, drawing on current trends and real-world experiences. The show is designed for educators, professionals, and anyone interested in understanding the practical and ethical dimensions of AI in modern work and academic settings.</description>
    <copyright>2026 OpenPod</copyright>
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    <podcast:locked>yes</podcast:locked>
    <language>en</language>
    <pubDate>Sun, 21 Jun 2026 16:38:55 -0700</pubDate>
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    <link>https://openpod.app</link>
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      <title>Co-Intelligence Living and Working with AI</title>
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    <itunes:type>serial</itunes:type>
    <itunes:author>Co-Intelligence Productions</itunes:author>
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    <itunes:summary>This podcast features in-depth conversations between two hosts exploring the evolving role of artificial intelligence in knowledge work and higher education. Each episode examines how AI is reshaping professional practices, learning environments, and human collaboration, drawing on current trends and real-world experiences. The show is designed for educators, professionals, and anyone interested in understanding the practical and ethical dimensions of AI in modern work and academic settings.</itunes:summary>
    <itunes:subtitle>This podcast features in-depth conversations between two hosts exploring the evolving role of artificial intelligence in knowledge work and higher education.</itunes:subtitle>
    <itunes:keywords>artificial-intelligence,higher-education,knowledge-work,ai-ethics,digital-transformation,human-ai-collaboration,professional-development</itunes:keywords>
    <itunes:owner>
      <itunes:name>openpod.app</itunes:name>
      <itunes:email>info@openpod.app</itunes:email>
    </itunes:owner>
    <itunes:complete>No</itunes:complete>
    <itunes:explicit>No</itunes:explicit>
    <item>
      <title>Rethinking Knowledge in the Age of Language Models</title>
      <itunes:episode>1</itunes:episode>
      <podcast:episode>1</podcast:episode>
      <itunes:title>Rethinking Knowledge in the Age of Language Models</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
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      <link>https://cointelligence.transistor.fm/s1/1</link>
      <description>
        <![CDATA[<p>When technology outpaces old ways of thinking. - Sleepless nights after witnessing new AI capabilities - The emotional impact of unexpected machine intelligence - How language models differ from traditional tools - The breakdown of old knowledge work models - The need for new frameworks to understand AI Timestamps will be added after transcription.</p>]]>
      </description>
      <content:encoded>
        <![CDATA[<p>When technology outpaces old ways of thinking. - Sleepless nights after witnessing new AI capabilities - The emotional impact of unexpected machine intelligence - How language models differ from traditional tools - The breakdown of old knowledge work models - The need for new frameworks to understand AI Timestamps will be added after transcription.</p>]]>
      </content:encoded>
      <pubDate>Mon, 20 Apr 2026 15:37:21 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/0fd84a66/cb1ee789.mp3" length="449117" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>38</itunes:duration>
      <itunes:summary>This episode explores the impact of advanced language models on how people perceive knowledge and work. The conversation highlights the unpredictability and novelty of these systems, challenging traditional ways of understanding intelligence. Listeners gain insight into the emotional and intellectual responses that arise when technology surpasses expectations and established frameworks.</itunes:summary>
      <itunes:subtitle>This episode explores the impact of advanced language models on how people perceive knowledge and work. The conversation highlights the unpredictability and novelty of these systems, challenging traditional ways of understanding intelligence. Listeners ga</itunes:subtitle>
      <itunes:keywords>ai,language-models,technology,knowledge,future,work,psychology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Alien Minds and the Limits of Understanding</title>
      <itunes:episode>6</itunes:episode>
      <podcast:episode>6</podcast:episode>
      <itunes:title>Alien Minds and the Limits of Understanding</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">6e7157ac-c6b5-4f74-b6be-6ec5beca22c9</guid>
      <link>https://cointelligence.transistor.fm/s1/6</link>
      <description>
        <![CDATA[What if an alien mind never needed sleep?
- Rethinking sleep and awareness in non-human intelligence
- Early reactions to advanced language models
- The line between tool and companion blurs
- Why language models feel unpredictable and strange
- Adapting to exponential knowledge growth
- Building flexible frameworks for uncertain times
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[What if an alien mind never needed sleep?
- Rethinking sleep and awareness in non-human intelligence
- Early reactions to advanced language models
- The line between tool and companion blurs
- Why language models feel unpredictable and strange
- Adapting to exponential knowledge growth
- Building flexible frameworks for uncertain times
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:41:37 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/1a5678d9/f62ac16f.mp3" length="4659631" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>389</itunes:duration>
      <itunes:summary>This episode explores the concept of alien intelligence, drawing parallels between non-human cognition and the rise of advanced language models. The discussion covers how these systems differ from human thought, the challenges of unpredictability, and the shift from memorization to adaptive learning. Listeners gain insight into why traditional frameworks struggle to keep pace with rapid knowledge growth and how individuals and teams can build resilience in an era of constant change.</itunes:summary>
      <itunes:subtitle>This episode explores the concept of alien intelligence, drawing parallels between non-human cognition and the rise of advanced language models. The discussion covers how these systems differ from human thought, the challenges of unpredictability, and the</itunes:subtitle>
      <itunes:keywords>ai,cognition,adaptation,language-models,uncertainty,frameworks,teams</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Four Rules for Working with AI</title>
      <itunes:episode>8</itunes:episode>
      <podcast:episode>8</podcast:episode>
      <itunes:title>Four Rules for Working with AI</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">19d57013-1abd-4524-96ed-f7aa2968fcf5</guid>
      <link>https://cointelligence.transistor.fm/s1/8</link>
      <description>
        <![CDATA[How do you work with a mind you didn’t evolve with?
- Why alignment with AI is urgent, not abstract
- Making AI a default participant, not a last resort
- The human’s role: collaborator, not just supervisor
- Assigning personas to AI for better results
- Why today’s AI is the worst you’ll ever use
- Building habits for a future with smarter systems
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[How do you work with a mind you didn’t evolve with?
- Why alignment with AI is urgent, not abstract
- Making AI a default participant, not a last resort
- The human’s role: collaborator, not just supervisor
- Assigning personas to AI for better results
- Why today’s AI is the worst you’ll ever use
- Building habits for a future with smarter systems
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:41:42 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/a646ca12/8d7aab4a.mp3" length="6886191" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>574</itunes:duration>
      <itunes:summary>This episode explores the practical realities of collaborating with artificial intelligence in daily work. The conversation covers the importance of proactive engagement, the necessity of human oversight, and the value of assigning clear roles to AI systems. Listeners will learn why current AI is the least capable they’ll ever use, how to build effective habits for the future, and what it means to treat AI as both a partner and a tool in evolving workflows.</itunes:summary>
      <itunes:subtitle>This episode explores the practical realities of collaborating with artificial intelligence in daily work. The conversation covers the importance of proactive engagement, the necessity of human oversight, and the value of assigning clear roles to AI syste</itunes:subtitle>
      <itunes:keywords>ai,alignment,collaboration,productivity,habits,technology,future</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Gains and Gaps at the Technological Frontier</title>
      <itunes:episode>10</itunes:episode>
      <podcast:episode>10</podcast:episode>
      <itunes:title>Gains and Gaps at the Technological Frontier</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">6a083e7d-96bf-4193-bf76-f5fbd8bc5c56</guid>
      <link>https://cointelligence.transistor.fm/s1/10</link>
      <description>
        <![CDATA[How do new tools change the pace and quality of work?
- Measurable productivity and quality gains inside the frontier
- Why structured tasks benefit more than creative ones
- The uneven impact of AI on different skill levels
- Risks of over-reliance on opaque systems
- The jagged, unpredictable nature of technological progress
- Strategies for adapting to shifting expectations
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[How do new tools change the pace and quality of work?
- Measurable productivity and quality gains inside the frontier
- Why structured tasks benefit more than creative ones
- The uneven impact of AI on different skill levels
- Risks of over-reliance on opaque systems
- The jagged, unpredictable nature of technological progress
- Strategies for adapting to shifting expectations
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:41:47 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/c3ccd39d/c538f605.mp3" length="25353628" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>2113</itunes:duration>
      <itunes:summary>This episode explores how advances in technology, particularly AI, impact productivity, quality, and workplace dynamics. Listeners learn why gains are uneven, how the technological frontier shifts expectations, and what happens when tools don’t fit the task. The discussion covers the jagged nature of progress, the risks of over-reliance on opaque systems, and the ways teams adapt to both breakthroughs and setbacks in rapidly changing environments.</itunes:summary>
      <itunes:subtitle>This episode explores how advances in technology, particularly AI, impact productivity, quality, and workplace dynamics. Listeners learn why gains are uneven, how the technological frontier shifts expectations, and what happens when tools don’t fit the ta</itunes:subtitle>
      <itunes:keywords>ai,productivity,workplace,automation,technology,adaptation,risk,progress</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>How Personas Shape AI Effectiveness and Human Connection</title>
      <itunes:episode>12</itunes:episode>
      <podcast:episode>12</podcast:episode>
      <itunes:title>How Personas Shape AI Effectiveness and Human Connection</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">d5fdbf59-c86d-43c5-a517-be4c1a39b6d5</guid>
      <link>https://cointelligence.transistor.fm/s1/12</link>
      <description>
        <![CDATA[How personas transform AI interactions and user experiences.
- Why personas make AI more predictable and effective
- The role of consistency and trust in AI-user relationships
- When persona prompting backfires or mismatches context
- The psychological impact of daily chatbot use
- Institutions tracking and responding to AI-related loneliness
- Balancing digital comfort with real-world connection
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[How personas transform AI interactions and user experiences.
- Why personas make AI more predictable and effective
- The role of consistency and trust in AI-user relationships
- When persona prompting backfires or mismatches context
- The psychological impact of daily chatbot use
- Institutions tracking and responding to AI-related loneliness
- Balancing digital comfort with real-world connection
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:41:53 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/ef9d75da/98929ed5.mp3" length="8725970" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>728</itunes:duration>
      <itunes:summary>This episode explores how assigning personas to AI systems influences their effectiveness, user trust, and the dynamics of human-AI relationships. The discussion covers the impact of persona prompts on response quality, the psychological effects of interacting with AI as if it were human, and the emerging challenges around loneliness and social connection in a world increasingly mediated by digital companions.</itunes:summary>
      <itunes:subtitle>This episode explores how assigning personas to AI systems influences their effectiveness, user trust, and the dynamics of human-AI relationships. The discussion covers the impact of persona prompts on response quality, the psychological effects of intera</itunes:subtitle>
      <itunes:keywords>ai,personas,trust,loneliness,chatbots,psychology,digital-relationships,technology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>How AI Changed the Blank Page</title>
      <itunes:episode>13</itunes:episode>
      <podcast:episode>13</podcast:episode>
      <itunes:title>How AI Changed the Blank Page</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">21760eaa-5bf3-4f9b-b2f7-714194a972f3</guid>
      <link>https://cointelligence.transistor.fm/s1/13</link>
      <description>
        <![CDATA[AI is reshaping how people approach creative projects across media.
- Three patterns of human-AI creative collaboration
- Multimodal AI: generating images, video, and audio together
- The evolving role of prompts in creative workflows
- Challenges of ownership, originality, and choice overload
- How professionals and amateurs adapt to AI-driven tools
- The shifting meaning of the "blank page" in creative work
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[AI is reshaping how people approach creative projects across media.
- Three patterns of human-AI creative collaboration
- Multimodal AI: generating images, video, and audio together
- The evolving role of prompts in creative workflows
- Challenges of ownership, originality, and choice overload
- How professionals and amateurs adapt to AI-driven tools
- The shifting meaning of the "blank page" in creative work
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:41:58 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/0ccf4084/b385876f.mp3" length="5051141" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>421</itunes:duration>
      <itunes:summary>This episode explores how generative AI is transforming creative work, from drafting digital ads to composing music videos. The discussion covers patterns of human-AI collaboration, the rise of multimodal tools, and the shifting challenges of creativity in an era where prompts replace blank pages. Listeners gain insight into how professionals and amateurs alike adapt to new workflows, balancing inspiration, control, and originality as AI becomes a creative partner.</itunes:summary>
      <itunes:subtitle>This episode explores how generative AI is transforming creative work, from drafting digital ads to composing music videos. The discussion covers patterns of human-AI collaboration, the rise of multimodal tools, and the shifting challenges of creativity i</itunes:subtitle>
      <itunes:keywords>ai,creativity,generative-models,multimodal,workflow,design,music,video</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Centaurs, Cyborgs, and the Rise of Agentic AI at Work</title>
      <itunes:episode>16</itunes:episode>
      <podcast:episode>16</podcast:episode>
      <itunes:title>Centaurs, Cyborgs, and the Rise of Agentic AI at Work</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">95f0c38b-8476-48cb-8420-7b853e8e950e</guid>
      <link>https://cointelligence.transistor.fm/s1/16</link>
      <description>
        <![CDATA[How AI is reshaping teamwork and job roles.
- Centaur workflows: dividing tasks between humans and AI
- Cyborg workflows: tightly blending human and AI contributions
- Agentic AI: digital coworkers that take action
- The shift to usage-based software pricing
- Shadow AI and its impact on workplace trust
- Adapting to new collaboration models with AI
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[How AI is reshaping teamwork and job roles.
- Centaur workflows: dividing tasks between humans and AI
- Cyborg workflows: tightly blending human and AI contributions
- Agentic AI: digital coworkers that take action
- The shift to usage-based software pricing
- Shadow AI and its impact on workplace trust
- Adapting to new collaboration models with AI
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:05 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/e77e7939/64b9e9dd.mp3" length="7834460" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>653</itunes:duration>
      <itunes:summary>This episode explores how AI is transforming workplace roles, from digital partners that boost productivity to agentic systems capable of executing tasks autonomously. Listeners will learn about centaur and cyborg workflows, the emergence of new job titles, the impact of usage-based software pricing, and the phenomenon of shadow AI. The discussion highlights both the opportunities and challenges as organizations adapt to increasingly collaborative and independent AI tools.</itunes:summary>
      <itunes:subtitle>This episode explores how AI is transforming workplace roles, from digital partners that boost productivity to agentic systems capable of executing tasks autonomously. Listeners will learn about centaur and cyborg workflows, the emergence of new job title</itunes:subtitle>
      <itunes:keywords>ai,workplace,productivity,automation,centaur,cyborg,agentic,software-pricing</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Adaptive Assessment and the Future of Learning</title>
      <itunes:episode>18</itunes:episode>
      <podcast:episode>18</podcast:episode>
      <itunes:title>Adaptive Assessment and the Future of Learning</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">6b136b31-55f7-4ded-b17d-cce32a6fc232</guid>
      <link>https://cointelligence.transistor.fm/s1/18</link>
      <description>
        <![CDATA[AI is transforming how students are assessed and how learning is measured.
- Personalized quizzes and adaptive feedback in classrooms
- The role of AI tutors in boosting student performance
- Balancing oral exams, handwritten essays, and digital tools
- Rethinking assessment in the age of AI and plagiarism detectors
- Shifting focus from final grades to the learning journey
- The future of motivation and transparency in education
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[AI is transforming how students are assessed and how learning is measured.
- Personalized quizzes and adaptive feedback in classrooms
- The role of AI tutors in boosting student performance
- Balancing oral exams, handwritten essays, and digital tools
- Rethinking assessment in the age of AI and plagiarism detectors
- Shifting focus from final grades to the learning journey
- The future of motivation and transparency in education
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:11 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/0c1cdfa1/2cb0e7f1.mp3" length="5807246" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>484</itunes:duration>
      <itunes:summary>This episode explores how AI-driven assessment tools are reshaping education, from personalized quizzes to real-time feedback and the blending of traditional methods with new technology. The discussion covers the impact on student motivation, the evolving definition of cheating, and the shift toward valuing the learning process over final results. Listeners gain insight into the challenges and opportunities as classrooms move away from one-size-fits-all exams toward adaptive, continuous assessment.</itunes:summary>
      <itunes:subtitle>This episode explores how AI-driven assessment tools are reshaping education, from personalized quizzes to real-time feedback and the blending of traditional methods with new technology. The discussion covers the impact on student motivation, the evolving</itunes:subtitle>
      <itunes:keywords>education,ai,assessment,motivation,adaptive-learning,edtech,feedback,pedagogy</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>How AI Is Changing Coaching and Ethics</title>
      <itunes:episode>20</itunes:episode>
      <podcast:episode>20</podcast:episode>
      <itunes:title>How AI Is Changing Coaching and Ethics</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">8d6cf2f5-4b8c-43c4-a445-2dc7a2190dee</guid>
      <link>https://cointelligence.transistor.fm/s1/20</link>
      <description>
        <![CDATA[AI is reshaping how people seek advice, learn, and build ethical awareness.
- Teens using AI for homework and feedback
- The ASK framework for evaluating AI advice
- Importance of feedback, scaffolding, and deliberate practice
- SIFT method for fact-checking AI claims
- Teaching ethics and critical thinking with AI in schools
- Balancing technology with human wisdom and empathy
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[AI is reshaping how people seek advice, learn, and build ethical awareness.
- Teens using AI for homework and feedback
- The ASK framework for evaluating AI advice
- Importance of feedback, scaffolding, and deliberate practice
- SIFT method for fact-checking AI claims
- Teaching ethics and critical thinking with AI in schools
- Balancing technology with human wisdom and empathy
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:18 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/7b853182/02cc8523.mp3" length="6131365" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>511</itunes:duration>
      <itunes:summary>This episode explores the evolving role of AI as a coach and advisor, highlighting how chatbots are influencing learning, feedback, and ethical decision-making. The discussion covers practical frameworks for evaluating AI guidance, the importance of feedback and scaffolding, and the challenges of building trust and critical thinking skills in an AI-driven world. Listeners gain insights into how awareness, skills, and knowledge shape responsible AI use, especially in educational settings.</itunes:summary>
      <itunes:subtitle>This episode explores the evolving role of AI as a coach and advisor, highlighting how chatbots are influencing learning, feedback, and ethical decision-making. The discussion covers practical frameworks for evaluating AI guidance, the importance of feedb</itunes:subtitle>
      <itunes:keywords>ai,coaching,education,ethics,feedback,critical-thinking,trust,literacy</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Shadow AI and the Policy Gap</title>
      <itunes:episode>22</itunes:episode>
      <podcast:episode>22</podcast:episode>
      <itunes:title>Shadow AI and the Policy Gap</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">532de17d-2425-4255-8916-27ad6b6bbc36</guid>
      <link>https://cointelligence.transistor.fm/s1/22</link>
      <description>
        <![CDATA[When rules lag behind, shadow systems emerge.
- The slow pace of policy versus rapid tech change
- Secret cyborgs and shadow AI adoption in workplaces
- Risks of cognitive offloading and skill erosion
- Social impacts: loneliness and reduced collaboration
- The scramble to update policies and its consequences
- The need for flexible adaptation over rigid rules
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[When rules lag behind, shadow systems emerge.
- The slow pace of policy versus rapid tech change
- Secret cyborgs and shadow AI adoption in workplaces
- Risks of cognitive offloading and skill erosion
- Social impacts: loneliness and reduced collaboration
- The scramble to update policies and its consequences
- The need for flexible adaptation over rigid rules
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:23 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/1112cd81/eb934f1c.mp3" length="6115368" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>510</itunes:duration>
      <itunes:summary>This episode explores the widening gap between rapid technology adoption and slow-moving institutional policies, focusing on the rise of "shadow AI" in workplaces and schools. Listeners will hear about the risks of unapproved AI use, the erosion of human skills, and the social impact of automation. The discussion highlights the challenges of balancing innovation with compliance, and considers how organizations can adapt without losing trust or human connection.</itunes:summary>
      <itunes:subtitle>This episode explores the widening gap between rapid technology adoption and slow-moving institutional policies, focusing on the rise of "shadow AI" in workplaces and schools. Listeners will hear about the risks of unapproved AI use, the erosion of human </itunes:subtitle>
      <itunes:keywords>ai,automation,policy,workplace,education,adaptation,technology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>How Small Language Models Are Changing Everyday Tech</title>
      <itunes:episode>24</itunes:episode>
      <podcast:episode>24</podcast:episode>
      <itunes:title>How Small Language Models Are Changing Everyday Tech</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">119db6be-0da4-4e61-ab91-e6651a524f28</guid>
      <link>https://cointelligence.transistor.fm/s1/24</link>
      <description>
        <![CDATA[Machines are learning to sense the world in new ways.
- Multimodal models blend images, audio, and text
- Small language models run on phones and laptops
- Deep research tools filter massive data sets
- Cross-modal reasoning and its challenges
- Vibe coding and intent-driven programming
- The evolving role of human oversight
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[Machines are learning to sense the world in new ways.
- Multimodal models blend images, audio, and text
- Small language models run on phones and laptops
- Deep research tools filter massive data sets
- Cross-modal reasoning and its challenges
- Vibe coding and intent-driven programming
- The evolving role of human oversight
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:29 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/7c12fb3e/de28e1f9.mp3" length="5596914" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>467</itunes:duration>
      <itunes:summary>Multimodal AI models now process images, audio, and text together, making advanced analysis accessible beyond large labs. Small language models run efficiently on personal devices, enabling offline use and improved privacy. The episode explores how these technologies impact research, creativity, and daily interactions, highlighting both their capabilities and limitations. Listeners gain insight into the evolving relationship between humans and intelligent systems, including the rise of "vibe coding" and the importance of human oversight.</itunes:summary>
      <itunes:subtitle>Multimodal AI models now process images, audio, and text together, making advanced analysis accessible beyond large labs. Small language models run efficiently on personal devices, enabling offline use and improved privacy. The episode explores how these </itunes:subtitle>
      <itunes:keywords>ai,multimodal,language-models,research,privacy,coding,technology,automation</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Power, Scarcity, and the AI Bubble</title>
      <itunes:episode>26</itunes:episode>
      <podcast:episode>26</podcast:episode>
      <itunes:title>Power, Scarcity, and the AI Bubble</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">2001906e-0a0f-47bd-b916-4a21f3725493</guid>
      <link>https://cointelligence.transistor.fm/s1/26</link>
      <description>
        <![CDATA[When water costs more than coffee, the world is changing.
- Surging water and housing costs reshape cities
- The generative AI bubble and its economic risks
- National AI models and digital sovereignty
- The hidden water footprint of AI technology
- Algorithmic justice and the challenge of accountability
- How power, scarcity, and technology intersect in daily life
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[When water costs more than coffee, the world is changing.
- Surging water and housing costs reshape cities
- The generative AI bubble and its economic risks
- National AI models and digital sovereignty
- The hidden water footprint of AI technology
- Algorithmic justice and the challenge of accountability
- How power, scarcity, and technology intersect in daily life
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:35 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/1df7d042/01219185.mp3" length="5917575" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>493</itunes:duration>
      <itunes:summary>This episode explores the rising costs of essential resources like water and housing, the volatility of the generative AI market, and the growing trend of national AI models. The discussion covers the hidden environmental impacts of AI, such as water usage, and delves into the challenges of algorithmic justice and accountability. Listeners gain insight into how these interconnected forces shape daily life, influence sovereignty, and affect access to basic needs in an increasingly complex world.</itunes:summary>
      <itunes:subtitle>This episode explores the rising costs of essential resources like water and housing, the volatility of the generative AI market, and the growing trend of national AI models. The discussion covers the hidden environmental impacts of AI, such as water usag</itunes:subtitle>
      <itunes:keywords>ai,water,housing,sovereignty,technology,justice,environment</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Four Futures for Artificial Intelligence</title>
      <itunes:episode>27</itunes:episode>
      <podcast:episode>27</podcast:episode>
      <itunes:title>Four Futures for Artificial Intelligence</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">e86a3d7a-62f5-42d7-a530-421a835054ce</guid>
      <link>https://cointelligence.transistor.fm/s1/27</link>
      <description>
        <![CDATA[AI is no longer just a tool—it's a character in our lives.
- Kids interact with AI as companions and storytellers
- Four possible futures for AI: replacement, amplification, invisibility, partnership
- Workplace shifts: new roles and creative collaboration with AI
- Human agency and the risks of invisible AI decision-making
- The evolving role of "human in the loop" at scale
- Responsibility and values in shaping AI's future
Timestamps will be added after transcription.]]>
      </description>
      <content:encoded>
        <![CDATA[AI is no longer just a tool—it's a character in our lives.
- Kids interact with AI as companions and storytellers
- Four possible futures for AI: replacement, amplification, invisibility, partnership
- Workplace shifts: new roles and creative collaboration with AI
- Human agency and the risks of invisible AI decision-making
- The evolving role of "human in the loop" at scale
- Responsibility and values in shaping AI's future
Timestamps will be added after transcription.]]>
      </content:encoded>
      <pubDate>Tue, 21 Apr 2026 05:42:42 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/505baa5b/3fd18102.mp3" length="5351456" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>446</itunes:duration>
      <itunes:summary>This episode explores how artificial intelligence is evolving from a simple tool to an active partner in daily life. The discussion covers shifting relationships with AI, the emergence of new roles, and the blurred boundaries between human and machine. Listeners will hear about the practical impacts of AI in work, creativity, and oversight, as well as the challenges of maintaining agency and responsibility in a world shaped by co-intelligence.</itunes:summary>
      <itunes:subtitle>This episode explores how artificial intelligence is evolving from a simple tool to an active partner in daily life. The discussion covers shifting relationships with AI, the emergence of new roles, and the blurred boundaries between human and machine. Li</itunes:subtitle>
      <itunes:keywords>artificial-intelligence,future-of-work,human-machine,co-intelligence,automation,creativity,agency,technology</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Stop Re Prompting AI with Markdown Skills</title>
      <itunes:episode>28</itunes:episode>
      <podcast:episode>28</podcast:episode>
      <itunes:title>Stop Re Prompting AI with Markdown Skills</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">bd8b8f6a-7914-4121-94fc-f8ce9a17d3f3</guid>
      <link>https://cointelligence.transistor.fm/s1/28</link>
      <description>
        <![CDATA[]]>
      </description>
      <content:encoded>
        <![CDATA[]]>
      </content:encoded>
      <pubDate>Sat, 20 Jun 2026 10:54:18 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/28ced5f5/8134cbb0.mp3" length="5035931" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>313</itunes:duration>
      <itunes:summary>
        <![CDATA[]]>
      </itunes:summary>
      <itunes:keywords>artificial-intelligence,higher-education,knowledge-work,ai-ethics,digital-transformation,human-ai-collaboration,professional-development</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
    <item>
      <title>Co-Intelligence: Working With AI as a Partner</title>
      <itunes:episode>29</itunes:episode>
      <podcast:episode>29</podcast:episode>
      <itunes:title>Co-Intelligence: Working With AI as a Partner</itunes:title>
      <itunes:episodeType>full</itunes:episodeType>
      <guid isPermaLink="false">bd7acafa-0e1c-4acf-a454-53cd19c90a30</guid>
      <link>https://cointelligence.transistor.fm/s1/29</link>
      <description>
        <![CDATA[In this episode we explore how humans and AI can collaborate as partners. You bring judgment, context, and values; the model brings speed, breadth, and pattern recognition. Together, the goal is better human work—not less of it.]]>
      </description>
      <content:encoded>
        <![CDATA[In this episode we explore how humans and AI can collaborate as partners. You bring judgment, context, and values; the model brings speed, breadth, and pattern recognition. Together, the goal is better human work—not less of it.]]>
      </content:encoded>
      <pubDate>Sun, 21 Jun 2026 16:38:55 -0700</pubDate>
      <author>Co-Intelligence Productions</author>
      <enclosure url="https://media.transistor.fm/e61ddccb/e138e43c.mp3" length="203900" type="audio/mpeg"/>
      <itunes:author>Co-Intelligence Productions</itunes:author>
      <itunes:duration>22</itunes:duration>
      <itunes:summary>A short episode on treating AI as co-intelligence rather than replacement.</itunes:summary>
      <itunes:subtitle>A short episode on treating AI as co-intelligence rather than replacement.</itunes:subtitle>
      <itunes:keywords>AI,co-intelligence,human-AI collaboration,productivity</itunes:keywords>
      <itunes:explicit>No</itunes:explicit>
    </item>
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