Programme

ProposedWebinar

Healthy Technology Habits for Modern Work

Digital wellbeing requires more than simply reducing screen time. Explore practical approaches to managing notifications, creating focused work periods, setting digital boundaries, and building intentional technology habits that support personal wellbeing.

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ProposedWebinar

Digital Overload: When Everything Demands Your Attention

Notifications, messages, platforms, and constant information flows compete for our attention throughout the day. Explore how digital overload affects concentration, daily routines, and wellbeing, and how people can develop healthier boundaries with connected technology.

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ProposedWebinar

Are Your Digital Tools Shaping How You Work?

Digital tools do more than support tasks: their prompts, defaults, and rhythms can shape how often we check, switch focus, and respond. Explore how individuals can recognize technology-driven work patterns and make more intentional choices about attention, availability, and personal wellbeing.

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ProposedWebinar

When Productivity Becomes Unsustainable

Faster tools do not automatically create healthier or more sustainable work. Explore how workload design, performance expectations, insufficient recovery, and organizational norms can turn productivity gains into exhaustion—and how employers can protect wellbeing while pursuing results.

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ProposedWebinar

Staying Human in an Always-On Digital Workplace

Digital tools make work more connected and accessible, but they can also create expectations of constant availability. Explore how always-on communication, blurred boundaries, and technology-driven work habits affect wellbeing, relationships, and the human experience of work.

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ProposedDiscussion

Inclusive AI: Who Are We Designing For?

AI systems can unintentionally exclude people when their needs, languages, abilities, or circumstances are overlooked. Explore how inclusive design principles and community perspectives can support more accessible, equitable, and useful AI technologies.

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ProposedDiscussion

The AI Divide: Beyond Devices and Connectivity

Connectivity alone does not guarantee meaningful access to AI-enabled services and opportunities. Explore how computing resources, accessible interfaces, language coverage, data representation, service design, and institutional capacity are creating a new layer of digital inequality.

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ProposedDiscussion

Who Can Afford to Benefit from AI?

Access to AI's benefits depends on more than whether a tool is publicly available. Explore how cost, infrastructure, institutional support, language access, disability, and unequal resources can determine which communities gain meaningful opportunities from AI.

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ProposedWebinar

Before You Share It: A New Literacy for the AI Era

Sharing information online can amplify misleading or inaccurate content, even unintentionally. Explore practical habits for evaluating claims, recognizing emotional manipulation, checking context, and making more responsible decisions before reposting or distributing digital content.

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ProposedWebinar

Why Deepfakes Persuade Even When We Know They Exist

Awareness of deepfakes does not automatically protect people from their influence. Explore how emotional reactions, repetition, social context, and existing beliefs make synthetic media persuasive—and what media literacy can do to strengthen public resilience.

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ProposedWebinar

How Synthetic Media Exploits What We Expect to See

Synthetic media can appear convincing because it draws on familiar visual conventions, emotional cues, and assumptions about how authentic content should look. Explore how AI-generated media exploits these expectations and how stronger media-literacy habits can reduce manipulation.

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ProposedWebinar

Can Regulation Keep Up With AI?

AI capabilities evolve faster than many traditional policy processes. Explore how governments can balance innovation, public protection, accountability, and adaptability when developing rules for emerging technologies.

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ProposedWebinar

Europe's Digital Future: Innovation, Security and Technological Independence

Europe faces important choices about technological competitiveness, digital infrastructure, security, and dependence on external technology providers. Explore how innovation policy, digital sovereignty, and strategic investment influence Europe's digital future.

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ProposedWebinar

Whose Values Are Inside the Algorithm?

AI systems reflect choices about data, design, priorities, and acceptable outcomes. Explore how cultural assumptions, institutional interests, and competing values shape algorithmic behavior and its consequences.

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ProposedWebinar

Are Some Uses of AI Morally Unacceptable?

Some AI applications may remain ethically troubling even when they are legal, accurate, or efficient. Explore how autonomy, dignity, fairness, vulnerability, and social harm can help societies judge whether particular uses of AI should be rejected or constrained.

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ProposedWebinar

Just Because AI Can Do It, Should It?

Technical capability does not automatically justify use. Explore how ethical principles, potential harm, human dignity, and social consequences should influence decisions about where and how AI is deployed.

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ProposedWebinar

Can Moral Responsibility Be Shared with a Machine?

AI can shape harmful or unfair outcomes, but machines do not bear responsibility in the same way people and institutions do. Explore whether moral responsibility can be distributed across designers, organizations, users, and automated systems—and what must remain irreducibly human.

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ProposedDiscussion

Who Gets to Participate in an AI-Shaped Society?

As digital and AI-mediated systems become part of public services, communication, education, and everyday routines, participation may become easier for some people and harder for others. Explore how access, confidence, design, and social expectations shape inclusion in digital society.

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ProposedDiscussion

When Content Is Abundant, What Gets Heard?

Generative AI enables many more people and organizations to produce text, images, audio, and video at scale. Explore how content abundance changes public attention, creative participation, visibility, representation, and whose voices are heard in digital spaces.

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ProposedDiscussion

What Happens to Public Trust When Information Becomes Synthetic?

Synthetic media changes more than whether individual claims appear credible. Explore how widespread uncertainty about what is real can affect public institutions, shared knowledge, civic discussion, and people's willingness to participate in digital public life.

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ProposedWebinar

Creating Psychological Safety During Technology Change

Employees may hesitate to ask questions or express concerns during technological change. Explore how leaders can encourage participation, feedback, experimentation, and responsible learning through psychological safety.

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ProposedWebinar

The Informal Rules That Shape Transformation

Formal transformation plans operate alongside unwritten expectations about authority, risk, cooperation, and acceptable behavior. Explore how leaders can identify these informal rules, understand their influence, and align cultural signals with intended organizational change.

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ProposedWebinar

When New Technology Meets Old Organizational Norms

New tools enter workplaces shaped by established routines, status relationships, and unwritten rules. Explore how leaders can identify the cultural patterns influencing technology use and reshape norms without treating every adoption problem as employee resistance.

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ProposedWebinar

The Cultural Conditions for Responsible AI Adoption

Responsible AI adoption depends on the norms employees use when interpreting, questioning, disclosing, and learning from AI-supported work. Explore how leaders can establish shared expectations, model responsible behavior, strengthen trust, and make reflection part of everyday practice.

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ProposedWebinar

Experiment First or Wait? Making Better Technology Decisions

Leaders must decide when to test emerging technologies and when to wait for greater maturity. Explore how to assess uncertainty, design manageable experiments, evaluate results, and determine whether an innovation deserves wider adoption.

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ProposedWebinar

What Problem Is This Innovation Supposed to Solve?

Innovation efforts often begin with an attractive technology rather than a clearly defined organizational need. Explore how leaders can frame the problem, identify affected stakeholders, establish evidence of value, and define measurable outcomes before committing significant resources.

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ProposedWebinar

Building an Innovation Portfolio Beyond the Hype Cycle

Organizations rarely face a single innovation choice. Explore how leaders can balance incremental improvements, strategic experiments, and longer-term bets, allocate resources across different levels of uncertainty, and review the portfolio as evidence changes.

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ProposedWebinar

Diagnosing Human–Algorithm Disagreement

Disagreement between an expert and an algorithm may reveal missing context, model limitations, uncertain evidence, or human bias. Explore how leaders can diagnose the source of disagreement, compare confidence, seek disconfirming evidence, and determine when escalation or further review is necessary.

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ProposedWebinar

Designing Decision Rights for Human-AI Systems

Organizations need more than a general principle of human oversight. Explore how leaders can classify decisions by consequences, reversibility, uncertainty, and value conflict, then assign clear authority to recommend, review, challenge, approve, or decide.

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ProposedWebinar

Who Owns AI Policy Implementation Across a University?

University AI policies often involve academic leadership, faculty development, student services, technology teams, research offices, and governance bodies. Explore how leaders can assign responsibilities, coordinate implementation, resolve gaps, and monitor whether institutional expectations are taking effect.

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ProposedWebinar

What Should University Leaders Decide About AI Now?

Universities face urgent decisions about AI adoption, teaching, research, assessment, and institutional responsibility. Explore which leadership decisions require immediate attention and how institutions can establish clear priorities without rushing into reactive policies.

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ProposedWebinar

Building the Leadership Coalition for Institutional AI Change

Institutional AI readiness requires coordinated leadership across academic, administrative, technology, and governance functions. Explore how university leaders can assign ownership, align priorities, resolve competing concerns, and establish a shared programme of institutional action.

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ProposedWebinar

Redesigning Work After Technology Goes Live

Technology implementation is only the beginning of organizational change. Explore how leaders can redesign workflows, clarify responsibilities, reinforce new practices, and help employees turn new tools into sustainable ways of working.

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ProposedWebinar

Change Fatigue: When Transformation Never Stops

Constant initiatives and shifting priorities can overwhelm employees. Explore how leaders recognize change fatigue, prioritize transformation efforts, and protect team capacity during prolonged change.

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ProposedWebinar

Why People Resist Technology—and What Leaders Can Do About It

Resistance to technology is not always unwillingness to change. Explore how uncertainty, trust, workplace habits, and communication influence adoption, and how leaders can respond constructively.

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ProposedWebinar

Leading People Through Continuous Change

Organizations face ongoing technological, structural, and cultural changes. Explore how leaders can provide clarity, maintain trust, support employees, and build adaptability when change becomes continuous.

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ProposedWebinar

The Leadership Review: Challenging AI Recommendations Before Acting

AI recommendations can influence important organizational choices, but leaders still need a disciplined review process before acting. Explore how to test assumptions, examine uncertainty, consider affected stakeholders, and document the reasoning behind a final decision.

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ProposedWebinar

Leading When the Data Isn't the Decision

Data can inform organizational choices without capturing every human, ethical, or contextual consideration. Explore how leaders can combine quantitative evidence with professional judgment, stakeholder perspectives, and organizational responsibility.

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ProposedWebinar

When Technology Gives You a Signal, Not an Answer

Technology can identify patterns, risks, and recommendations, but these signals do not automatically determine the right decision. Explore how leaders can interpret technological evidence, evaluate context, and exercise responsible human judgment.

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ProposedWebinar

When Culture Meets Remote Work

Remote work can amplify differences in cultural expectations, communication habits, and approaches to teamwork. Explore how distributed teams can navigate cultural differences, build trust, and develop inclusive collaboration practices.

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ProposedWebinar

Communication Skills for Global Teams

Global teams bring together different languages, communication styles, and professional expectations. Explore how professionals can communicate clearly, reduce misunderstandings, and strengthen collaboration across diverse teams.

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ProposedWebinar

Working Across Borders in a Digital World

Digital technology allows professionals to collaborate across countries and time zones, but effective global work requires more than connectivity. Explore the opportunities, challenges, and practical skills needed for successful international collaboration.

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ProposedWebinar

How Do You Know Whether Training Actually Worked?

Attendance and satisfaction do not necessarily demonstrate training impact. Explore how organizations can evaluate learning outcomes, behavior change, practical application, and workplace performance.

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ProposedWebinar

Building a Culture of Continuous Learning

Workplace skills must evolve alongside business needs. Explore how organizations can encourage curiosity, knowledge sharing, professional development, and everyday learning.

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ProposedWebinar

From Training to Daily Practice: Building Learning Transfer Systems

Training creates value only when employees apply learning in their daily work. Explore how organizations can combine manager support, practice opportunities, coaching, reinforcement, and workplace processes to build reliable learning transfer.

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ProposedWebinar

Reskilling for the AI Era

AI is changing workplace responsibilities and skill requirements. Explore how organizations can identify skill gaps, prioritize reskilling, and help employees adapt to AI-enabled roles.

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ProposedWebinar

Technical Skills Change. What Should You Keep Learning?

Technical tools and job requirements evolve rapidly. Explore how professionals can identify durable foundations, update technical competencies, and make practical decisions about continuous learning.

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ProposedWebinar

The Skills AI Cannot Easily Replace

AI can automate many activities, but some professional capabilities remain difficult to replicate. Explore the importance of interpersonal judgment, complex problem-solving, ethical reasoning, and context-sensitive decision-making.

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ProposedWebinar

How to Practice Judgment When AI Produces the First Draft

When AI produces an initial answer, professional value shifts toward evaluating assumptions, identifying missing context, comparing alternatives, and deciding what is fit for use. Explore practical ways to strengthen judgment in AI-assisted work.

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ProposedWebinar

Your Job Title May Change. Will Your Skills Travel?

Job titles and responsibilities change, but many professional capabilities remain valuable across roles and industries. This session explores how individuals can identify transferable skills, communicate their value, and use existing experience to pursue new career opportunities.

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ProposedWebinar

Building a Career When Roles Keep Changing

Traditional career paths are becoming less predictable as industries and job responsibilities evolve. This session explores how professionals can navigate career transitions, identify new opportunities, and build adaptable career strategies without relying on fixed job titles.

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ProposedWebinar

Where Does AI Actually Save Time at Work?

AI promises productivity improvements, but real benefits depend on how tools are used. Explore practical workplace applications, workflow improvements, hidden costs, and ways to evaluate whether AI genuinely saves time.

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ProposedWebinar

The AI Colleague: What Should Humans Still Own?

As AI becomes more capable, the boundaries between automated assistance and human responsibility become less clear. Explore which workplace decisions, relationships, and responsibilities should remain under human ownership.

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ProposedWebinar

Building a Human-AI Task Map for Everyday Work

Effective AI adoption requires more than deciding whether to automate. Explore a practical method for mapping workplace tasks according to risk, repeatability, verification needs, and the value of human judgment.

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ProposedWebinar

Preparing People for Jobs That Are Still Evolving

Career preparation often assumes stable job roles. Explore how educators, employers, and professionals can build adaptable capabilities, encourage lifelong learning, and prepare for changing employment demands.

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ProposedWebinar

Which Jobs Change First When AI Becomes Normal?

AI is transforming workplace tasks, but its effects vary across occupations. Explore which jobs may change earliest, how responsibilities could evolve, and how workers and employers can prepare.

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ProposedWebinar

What Will Work Look Like Five Years From Now?

AI, automation, and changing organizational expectations are reshaping work. Explore possible developments in professional roles, workplace collaboration, technology adoption, and future skills.

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ProposedWebinar

The Skills That Matter When Everything Is Changing

As technologies and job requirements evolve, professionals must reconsider which capabilities remain valuable. Explore adaptable skills, continuous learning, critical thinking, and competencies for navigating professional change.

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ProposedWebinar

From Presentation to Participation: Designing Better Training

Effective training requires more than polished presentations. This session explores how trainers and facilitators can create interactive learning experiences through purposeful activities, discussion, collaboration, and opportunities for participants to apply what they learn.

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ProposedWebinar

What Makes Professional Training Actually Work?

Delivering information does not automatically produce learning or improved performance. This session explores the factors that make professional training effective, including relevant objectives, participant engagement, practical application, feedback, and follow-through.

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ProposedWebinar

Helping Educators Move From AI Anxiety to AI Readiness

AI adoption can create uncertainty, resistance, and professional concerns among educators. This session explores how faculty development initiatives can build confidence, address concerns, encourage experimentation, and support responsible AI integration into teaching.

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ProposedWebinar

What Faculty Actually Need From AI Training

Many AI training initiatives focus on tools rather than educators' actual needs. This session explores how institutions can design relevant, practical, and sustainable faculty development programs that address teaching challenges, confidence gaps, and real classroom applications.

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ProposedWebinar

Preparing Faculty for AI-Enabled Education

As AI becomes increasingly embedded in education, faculty need more than general awareness of emerging technologies. This session explores the competencies, institutional support, and professional learning opportunities educators need to adapt confidently and responsibly.

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ProposedWebinar

Designing Learning Activities for Authentic Participation

Meaningful learning depends on what students actively do, not only on the work they submit. This session explores how educators can design activities that encourage inquiry, discussion, application, reflection, and genuine participation throughout the learning process.

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ProposedWebinar

Designing for Thinking, Not Just Answers

Learning is more than producing correct responses. This session explores how educators can design activities and learning experiences that develop reasoning, problem-solving, reflection, and deeper understanding, even when AI-generated answers are readily available.

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ProposedWebinar

Making Student Reasoning Visible in AI-Enabled Learning

When polished answers can be generated instantly, educators need learning activities that make students’ reasoning visible. This session explores process documentation, explanation, dialogue, iteration, and reflection as ways to help students demonstrate how their understanding develops.

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ProposedWebinar

Preparing Students to Question AI, Not Just Use It

Effective AI literacy requires more than generating answers. This session explores how students can evaluate AI-generated information, recognize limitations and potential errors, and develop habits of questioning and verification.

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ProposedWebinar

AI Is Available. But When Should Students Use It?

Having access to AI does not mean it is appropriate for every academic task. This session explores how students can decide when AI use supports learning, when it creates risks, and how to make responsible choices.

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ProposedWebinar

Using AI Without Losing Your Own Thinking

AI can support learning, but excessive reliance may weaken independent thinking. This session explores how students can use AI as a learning aid while maintaining critical reasoning, personal judgment, and authentic academic contribution.

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ProposedWebinar

What Should Students Actually Know About AI?

Students increasingly use AI tools, but knowing how to operate them is not the same as understanding their capabilities and limitations. This session explores the essential AI knowledge students need to become informed, responsible, and critical users.

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ProposedWebinar

What Do Students Actually Understand About Academic Integrity?

Students may know academic integrity policies without understanding how they apply in practice, particularly when using AI. This session explores gaps in student understanding and how educators can communicate expectations more clearly.

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ProposedWebinar

From Catching Misconduct to Building Integrity

Detecting misconduct matters, but preventing it requires more than identifying violations. This session explores education-centered approaches, clearer expectations, supportive learning environments, and meaningful student engagement.

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ProposedWebinar

Teaching Academic Integrity Beyond Detection

Academic integrity is often addressed through plagiarism checks, AI detection, and misconduct procedures. This session explores how educators can go beyond these measures to teach responsible academic practices, develop student understanding, and encourage ethical decision-making.

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ProposedWebinar

Does More Technology Actually Mean Better Learning?

Educational institutions continue to adopt new technologies, but greater technology use does not automatically lead to better learning. This session explores how educators can evaluate the educational value of digital tools and prioritize learning outcomes over technology adoption.

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ProposedWebinar

Designing Learning for an AI-Enabled Classroom

AI-powered tools are becoming part of everyday learning environments, creating new opportunities and challenges for educators. This session explores how learning experiences can be designed to incorporate AI thoughtfully while supporting learner engagement, critical thinking, and meaningful educational outcomes.

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ProposedWebinar

The Classroom After Generative AI

Generative AI is changing how students access information, complete assignments, and engage with learning. This session explores what the future university classroom could look like and how educators can create learning experiences that remain relevant, engaging, and meaningful.

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ProposedWebinar

Should Students Be Allowed to Use AI?

Universities and educators are navigating difficult questions about when and how students should use generative AI. This session explores responsible AI use in academic settings, the importance of clear expectations, and how educators can balance innovation with learning objectives and academic integrity.

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ProposedWebinar

Teaching When Students Have AI

Students increasingly have access to AI tools that can explain concepts, generate content, and support academic tasks. This session explores how university educators can adapt their teaching approaches while preserving critical thinking, meaningful participation, and authentic student learning.

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ProposedWebinar

Beyond the Essay: Rethinking Academic Assessment

Traditional essays remain valuable, but they are not the only way to evaluate academic learning. This session explores alternative assessment approaches that can encourage critical thinking, reflection, problem-solving, and authentic demonstrations of student knowledge.

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ProposedWebinar

What Should We Assess When Writing Can Be Automated?

As AI-generated writing becomes increasingly accessible, the relationship between written assignments and demonstrated learning is changing. This session explores which skills and learning outcomes educators should prioritize when writing alone may no longer provide sufficient evidence of understanding.

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ProposedWebinar

Designing Assessment When AI Can Produce the Answer

When AI can generate convincing responses to traditional assessment tasks, educators need to reconsider how they evaluate student learning. This session explores assessment approaches that emphasize thinking processes, evidence of understanding, and meaningful application.

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ProposedWebinar

The Assignment Has Changed

Generative AI can now complete many traditional academic assignments, raising questions about what these tasks actually measure. This session explores how educators can rethink assignments to better evaluate learning, reasoning, and authentic student contribution.

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ProposedWebinar

Who Is Actually Reading Your Research?

Research can be publicly available without necessarily reaching the people who could benefit from it. This session explores research audiences, scholarly engagement, and how researchers can better understand who discovers, reads, and uses their work.

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ProposedWebinar

From Publication to Impact

Publishing research is an important achievement, but meaningful impact often depends on what happens afterward. This session explores how scholarly work can move beyond publication to inform decisions, support innovation, influence practice, and contribute to wider societal value.

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ProposedWebinar

Search, AI and the Future of Academic Discovery

AI is transforming how scholarly information is searched, organized, and presented. This session explores the future of academic discovery, including the benefits, limitations, and responsibilities associated with AI-assisted research search tools.

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ProposedWebinar

The Library in the Age of AI Discovery

Academic libraries have long played a central role in helping people access reliable research. This session explores how AI-assisted discovery is influencing library services, information access, and the evolving role of libraries in supporting researchers and learners.

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ProposedWebinar

How Researchers Find Knowledge Is Changing

Traditional academic search methods are evolving as AI-powered discovery tools become more common. This session explores how researchers find scholarly information, what is changing in the discovery process, and the opportunities and challenges of emerging search technologies.

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ProposedWebinar

One Study, Many Languages, Wider Reach

Communicating research across languages can help scholarly knowledge reach new audiences and communities. This session explores multilingual dissemination, translation considerations, and approaches to expanding research reach while preserving accuracy and context.

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ProposedWebinar

Making Local Research Globally Discoverable

Research addressing local challenges can have relevance far beyond its original community, yet it may remain difficult for international audiences to find. This session explores how researchers can improve the visibility, accessibility, and international reach of locally produced knowledge.

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ProposedWebinar

Does Research Need to Be in English to Be Visible?

English dominates much of international academic publishing, raising questions about the visibility of research produced in other languages. This session explores the challenges faced by non-English scholarship and how research communities can support more inclusive approaches to global discovery.

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ProposedWebinar

Breaking the Language Barrier in Research Discovery

Valuable research is produced in many languages, but language barriers can prevent it from reaching relevant audiences. This session explores the challenges of cross-language research discovery and how researchers and institutions can improve access to knowledge across linguistic boundaries.

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ProposedWebinar

Verification Skills Every Researcher Now Needs

As AI makes information easier to generate and distribute, verifying scholarly claims becomes increasingly important. This session explores practical approaches to evaluating sources, checking citations, validating evidence, and maintaining confidence in research findings.

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ProposedWebinar

The Source Exists—but Does It Support the Claim?

Finding a legitimate source is only the first step in evaluating evidence. This session explores how researchers can determine whether cited material genuinely supports an argument, recognize misleading interpretations, and strengthen the connection between claims and evidence.

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ProposedWebinar

Can We Still Trust the Citation?

Citations can make academic work appear credible, but a reference does not automatically guarantee accuracy or reliability. This session explores the challenges of fabricated, inaccurate, and misleading citations, particularly in AI-assisted research, and what researchers should verify before trusting a reference.

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ProposedWebinar

Making Research More Reusable, Not Just Available

Research that is publicly available is not necessarily easy for others to understand, evaluate, or reuse. This session explores the importance of documentation, accessibility, context, and research practices that support meaningful knowledge reuse.

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ProposedWebinar

What Does Responsible Openness Look Like?

Open research creates opportunities for collaboration and knowledge sharing, but openness also involves ethical and practical responsibilities. This session explores how researchers can balance transparency, accessibility, privacy, and responsible research practices.

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ProposedWebinar

Open Research: Accessible Does Not Always Mean Discoverable

Making research openly accessible does not automatically ensure that people can find or understand it. This session explores the difference between availability and discoverability and how researchers can help their work reach wider audiences.

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ProposedWebinar

Open Science in the Age of AI

Artificial intelligence is changing how research is discovered, analyzed, and reused. This session explores what these developments mean for open science, research transparency, accessibility, and responsible knowledge sharing.

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ProposedWebinar

Scholarly Communication Beyond Journals and PDFs

Research communication is expanding beyond traditional journal articles and static documents. This session explores emerging approaches to sharing academic knowledge and how researchers can make their work more accessible, discoverable, and useful to different audiences.

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ProposedWebinar

The Research Paper Is Published. What Happens Next?

The publication of a research paper is an important milestone, but its journey does not end there. This session explores how research can reach relevant audiences, support knowledge exchange, and create opportunities for wider understanding and impact.

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ProposedWebinar

Is Publishing Enough Anymore?

Publishing research remains essential, but publication alone does not guarantee visibility, understanding, or impact. This session explores how scholarly communication is changing and what researchers should consider beyond getting their work published.

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ProposedWebinar

Are We Measuring Research Impact the Wrong Way?

Citations, publication counts, and other traditional metrics offer useful signals, but they do not always capture the full value of research. This session explores the limitations of conventional impact measurement and how institutions can think more broadly about research influence and contribution.

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ProposedWebinar

Research Assessment in a Changing Research Landscape

Research is evolving, but many assessment practices still rely on traditional measures of academic performance. This session explores how research evaluation can respond to changing research practices, emerging technologies, and broader expectations of scholarly contribution.

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ProposedWebinar

From Published to Discoverable: Closing the Visibility Gap

Publication is an important milestone, but it is not the end of the research journey. This session explores the gap between making research available and making it discoverable, accessible, and useful to wider audiences.

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ProposedWebinar

Can AI Find Your Research?

AI is changing how people search for and discover academic knowledge. This session explores how AI-assisted discovery may influence research visibility and what researchers should understand about making their work easier to find.

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ProposedWebinar

Why Good Research Still Goes Unnoticed

Publishing valuable research does not guarantee that the right audiences will discover it. This session explores the barriers that limit research visibility and what researchers can do to improve how their work is found and understood.

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ProposedDiscussion

When Writing Style Suddenly Changes: What Should We Do Next?

A sudden change in writing style may raise questions, but it does not automatically establish misconduct. This session explores how educators and academic reviewers can interpret writing-pattern changes responsibly, consider context, and determine appropriate next steps.

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ProposedDiscussion

Authorship in the Age of Generative AI

As AI becomes part of research and academic writing, institutions need to reconsider how authorship and contribution are understood. This session explores responsible AI assistance, attribution, transparency, and the evolving expectations surrounding academic authorship.

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ProposedDiscussion

Who Actually Wrote the Paper?

Generative AI is challenging traditional assumptions about academic authorship. This session explores what meaningful authorship means when AI can contribute to writing and why understanding human contribution, transparency, and verification matters.

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ProposedWebinar

Academic Misconduct or Responsible AI Use? Where Is the Boundary?

As AI becomes part of academic work, distinguishing acceptable assistance from misconduct is increasingly complex. This session explores how researchers and institutions can evaluate AI use through transparency, contribution, institutional expectations, and human judgment.

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ProposedWebinar

The New Integrity Risks Researchers Need to Recognize

AI-assisted research introduces new questions about transparency, attribution, evidence, and responsibility. This session explores emerging research integrity risks and the practical warning signs researchers should recognize.

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ProposedWebinar

When Research Looks Credible but Isn't

A polished research paper can contain convincing arguments, references, and evidence that do not withstand scrutiny. This session explores why apparent credibility is not enough and how researchers can evaluate claims, sources, and supporting evidence more carefully.

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ProposedWebinar

Research Integrity After Generative AI

Generative AI is changing how research is written, reviewed, and communicated. This session explores emerging integrity challenges and how researchers and institutions can respond through stronger verification, responsible practices, and informed judgment.

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ProposedWebinar

AI Changed the Threat Landscape. Are Organizations Ready?

AI is changing both the capabilities available to organizations and the risks they face. This session explores how the digital threat landscape is evolving and what organizations should consider when preparing for AI-enabled risks.

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ProposedWebinar

Building Digital Resilience in an AI-Driven World

As organizations become more dependent on digital systems and AI, resilience requires more than preventing individual incidents. This session explores how organizations can prepare for disruption, adapt to emerging risks, and build stronger digital resilience.

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ProposedWebinar

From Hype to Impact: Reading Technology Trends More Critically

Technology trends are often surrounded by bold predictions and exaggerated expectations. This session explores practical ways to evaluate emerging technologies by looking beyond hype toward evidence, adoption, limitations, and potential impact.

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ProposedWebinar

Which Emerging Technologies Actually Matter?

New technologies constantly compete for attention, but not every trend will create meaningful change. This session explores how to distinguish potentially transformative technologies from short-lived hype.

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ProposedWebinar

What Comes After the AI Boom?

AI currently dominates technology conversations, but innovation will not stop there. This session explores what may follow the current AI boom and how people and organizations can think more critically about the next wave of technological change.

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ProposedWebinar

Can You Prove Where That Information Came From?

Knowing where information originated can be as important as the information itself. This session explores provenance, source tracing, evidence, and why understanding the path from source to claim is becoming increasingly important.

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ProposedWebinar

Verification Is Becoming Everyone's Job

Verification is no longer only the responsibility of researchers, journalists, or specialists. This session explores why checking sources, claims, evidence, and context is becoming an essential skill for everyday professional and digital life.

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ProposedWebinar

Trust in the Age of AI-Generated Everything

AI can generate convincing text, images, audio, and other forms of content at enormous scale. This session explores what that means for trust and how people can make better judgments when authenticity is increasingly difficult to determine.

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ProposedWebinar

How Do We Know What to Trust Online?

Digital information is easier than ever to create and distribute, making credibility harder to judge. This session explores practical ways to evaluate sources, evidence, context, and credibility in increasingly complex online environments.

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ProposedWebinar

How Much AI Knowledge Does a Non-Technical Professional Need?

Professionals do not need to become AI engineers to work effectively with AI. This session explores the practical level of AI understanding non-technical professionals need to evaluate tools, question outputs, and make informed decisions.

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ProposedWebinar

Beyond Prompting: Understanding What AI Can and Cannot Do

Effective AI use requires more than knowing how to write a good prompt. This session explores the capabilities and limitations of AI and why understanding both is essential for making better decisions about when and how to use it.

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ProposedWebinar

AI Literacy: What Everyone Actually Needs to Know

AI literacy is becoming relevant far beyond technical roles. This session explores the essential knowledge people need to understand AI, question its outputs, recognize its limitations, and use it more responsibly.

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ProposedWebinar

Why Digital Transformation Projects Fail After Launch

Launching new technology does not guarantee lasting transformation. This session explores why digital initiatives often lose momentum after implementation and what organizations need to turn technology adoption into sustainable change.

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ProposedWebinar

From Digital Transformation to Digital Resilience

Digital transformation is not only about adopting new technology. Organizations also need the ability to adapt when technologies, risks, and expectations continue to change. This session explores the shift from transformation projects toward long-term digital resilience.

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ProposedWebinar

Before You Approve That AI Tool: What Should You Ask?

Adopting an AI tool should involve more than evaluating features and price. This session explores the questions organizations should ask about purpose, data, risk, accountability, reliability, and human oversight before adoption.

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ProposedWebinar

Building AI Governance People Can Actually Follow

Governance only works when people understand what it means for their everyday decisions. This session explores how organizations can create AI governance that is clear, practical, and usable.

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ProposedWebinar

Who Is Accountable When AI Makes the Recommendation?

AI can increasingly influence decisions, but accountability cannot simply be delegated to technology. This session explores where responsibility should sit when AI contributes to recommendations and decisions.

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ProposedWebinar

From AI Policy to Practice

AI policies can establish principles, but the real challenge is turning them into decisions people can apply in everyday work. This session explores how organizations can move from written AI policy to practical guidance and shared expectations.

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ProposedWebinar

Prompting Is Not the Skill: What Comes Next?

Knowing how to prompt AI is useful, but meaningful AI capability goes further. This session explores the judgment, verification, and critical thinking skills people need beyond prompting.

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ProposedWebinar

Working With Generative AI Without Losing Human Judgment

Generative AI can accelerate everyday work, but effective use still requires people to question, verify, interpret, and make decisions.

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ProposedWebinar

What Should We Actually Delegate to AI?

AI can perform more tasks than ever, but capability does not automatically mean delegation is appropriate. This session explores what we should delegate to AI and what should remain human-led.

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ProposedWebinar

Where Should Academic Institutions Draw the Line with AI?

As AI becomes part of academic work, institutions need clearer boundaries around where and how it should be used. This session explores responsible AI use, institutional expectations, human judgment, and academic integrity.

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ProposedWebinar

AI in Academia: From Experimentation to Everyday Practice

AI is moving from experimentation into everyday academic work. This session explores what that transition means for teaching, research, administration, expectations, and institutional practice.

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ProposedWebinar

What Does AI Readiness Actually Look Like in a University?

AI readiness goes beyond giving people access to AI tools. This session explores what institutions need in place to use AI responsibly and effectively.

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