Uso y desarrollo ético de la Inteligencia Artificial en la Universidad

Welcome to the First TIC Seminar of 2026

Introduction and Purpose

• The seminar is introduced as an opportunity for significant achievements in 2026, emphasizing well-being for all participants.

• This session focuses on initiatives from UNAM (National Autonomous University of Mexico), highlighting ongoing work in cutting-edge ICT topics.

Key Participants

• Notable speakers include:

• Dr. Ana Yuri Ramírez Molina: A pioneer in digital preservation and software development.

• Dr. Luz María Castañera de León: An expert in transforming ICT governance at higher education levels.

• M.Sc. María Teresa Ventura Miranda: Advocate for strategic software projects and IT management.

• M.Sc. Juan Manuel Castillejos Reyes: Promotes innovation and digital sustainability projects within the university context.

Discussion on Ethical Use of AI

Overview of the Initiative

• Dr. Ana Yuri expresses gratitude for the platform to discuss their initiative, which involved collaboration among various authors and contributors from DGETIC (General Directorate of Computing and Information Technologies).

• The project was initiated due to a surge in interest following the release of GPT-3.5 by OpenAI, marking a pivotal moment in AI interaction capabilities.

Contextual Background

• In response to GPT's impact, a working group was formed under Dr. Héctor Benítez to assess advancements in AI within academic settings, focusing on UNAM's contributions and experiences with technology integration.

• Concerns about AI replacing human roles emerged alongside excitement over its capabilities, reflecting both enthusiasm and apprehension regarding technological advancements in education and beyond.

Introduction to AI in Academia

The Emergence of AI Tools

• The rise of OpenAI tools has generated significant interest and concern, prompting discussions on their implications in various fields.

• AI is becoming increasingly useful in academia, research, and teaching, leading to both excitement and apprehension about its impact.

Concerns About AI Replacement

• There are fears that machines may replace human roles, raising questions about how individuals can differentiate their contributions from those of AI.

• This situation necessitates a reflective approach regarding the use of AI tools and the responsibilities that come with them.

Ethical Considerations

• The discussion emphasizes the importance of ethical principles in using AI technologies within academic settings.

• Ethics should not just be an area to promote but a fundamental aspect of professional conduct that must be integrated into daily practices.

Institutional Responsibility

• Universities recognize the need for responsible engagement with new technologies while maintaining core professional values.

• The UNAM (National Autonomous University of Mexico) aims to build upon existing frameworks rather than reinventing foundational concepts related to technology use.

Ongoing Dialogue on Ethics

• As technology evolves rapidly, continuous dialogue around ethical considerations remains crucial for adapting academic practices.

• The book discussed serves as a tangible resource for reflecting on these issues within the context of academia.

Engaging with the Community

Introduction to Further Discussions

• Acknowledgment is given to Dr. Nay Yuri for her coherent introduction, setting the stage for deeper exploration into ethical AI usage.

Availability of Resources

• Information will be provided later regarding where participants can access or download relevant materials related to this discussion.

Interactive Engagement

• An invitation is extended for participants to engage by sharing their thoughts on their current stance regarding ethical development in artificial intelligence.

Focus on Teaching and Research

• Transitioning into discussions led by Juan Manuel Castillejos Reyes about the role of artificial intelligence specifically in university teaching and research contexts.

Introduction to AI in Education

Overview of the Discussion

• The speaker expresses gratitude and introduces the topics covered in their book, emphasizing the importance of reflection on current educational practices.

• There is a growing concern regarding how rapidly evolving tools in universities impact teaching and research, leading to questions from faculty and students about their effectiveness.

The Role of AI Tools

• The discussion highlights that while AI tools are advancing across various fields, the focus remains on their application in education and research.

• AI can assist in content generation, enriching educational materials and providing updated resources for students.

Enhancing Learning Experiences

• Various AI applications support student learning by offering diverse methods for engagement and feedback.

• With an abundance of information available, educators can evaluate student submissions more efficiently, allowing for deeper exploration of subjects.

Challenges and Ethical Considerations

Data Privacy Concerns

• The use of learning analytics raises concerns about data privacy; personal information must be managed securely to align with university principles.

Algorithmic Bias Risks

• There is a risk of algorithmic bias affecting outcomes based on how data is fed into these systems; critical analysis is necessary to identify potential biases.

Cognitive Dependence on AI

• A cautionary note is raised about cognitive dependence on AI tools, which may lead users to accept outputs without further investigation or critical thinking.

Maintaining Academic Integrity

Importance of Proper Attribution

• Emphasizing academic integrity, it’s crucial for users to distinguish between original work and that generated by AI tools, ensuring proper references are maintained.

Understanding the Impact of Artificial Intelligence in Education

The Role of AI in Teaching

• The discussion highlights the importance of understanding how artificial intelligence (AI) is being utilized in education, particularly in teaching methodologies.

• It is noted that AI has significantly transformed contemporary teaching practices, necessitating adaptations to existing educational models and tools.

• A survey revealed that 49% of students are already using generative AI tools, indicating a minimal barrier to access these technologies for educational purposes.

• The increased adoption of AI tools calls for ethical frameworks within institutions to guide their use and ensure responsible integration into teaching practices.

• Emphasis is placed on maintaining an ethical foundation while leveraging AI tools, ensuring that educators critically assess the outputs generated by these technologies.

Research Applications of AI

• In research contexts, AI aids in processing large datasets efficiently, which can be time-consuming without such technology.

• The ability to synthesize data quickly allows researchers to obtain results more rapidly and supports predictive analysis and modeling efforts.

• While AI has been used prior to its recent surge in popularity, its capabilities have greatly enhanced research efficiency and effectiveness.

• Concerns regarding privacy and sensitive information protection arise as researchers utilize these tools; careful management is essential.

• Researchers must remain vigilant about biases inherent in AI systems due to the nature of data inputted into them.

Challenges Associated with AI Use

• There are risks related to transparency; users may not fully understand how data is processed within AI systems, leading to potential misinterpretations of results.

• This lack of clarity raises questions about accountability and the need for thorough investigation into how outcomes are derived from input data.

• A reference from a 2024 Oxford survey indicates widespread adoption among researchers globally; however, it underscores the necessity for verification processes when utilizing AI-generated insights.

Discussion on the Ethical Use of AI in Education

Concerns About Personal Data and Future Implications

• The majority view AI usage positively, but half express concerns about future implications regarding personal data usage and lack of explicit consent.

• There is a critical need to evaluate how AI affects our thinking processes and not blindly accept suggestions from these models.

Changing Educational Models

• AI is transforming teaching methods and research approaches, facilitating information management. This evolution raises ethical challenges that must be addressed to ensure safety and benefit for humanity.

• The discussion emphasizes the importance of forming individual opinions on these topics through reading relevant literature.

Community Engagement and Feedback

• Acknowledgment of active participation from various community members, including international viewers, highlights the global interest in this topic. Specific responses reflect diverse perspectives on adapting to AI's presence in education.

• Key insights shared by participants include the necessity for transparency, responsibility, innovation, awareness of regulations, and ethical considerations surrounding AI use in educational contexts.

Ethical Frameworks for AI

• The conversation transitions to discussing ethical frameworks guiding AI development and implementation within educational institutions. Emphasis is placed on aligning technology with humanistic values as highlighted by international documents like OECD principles (2019) and Beijing Consensus (2019).

• Historical context reveals that discussions around ethics in technology predate current advancements like ChatGPT; however, recent developments have intensified focus on these issues due to their widespread impact.

Principles Guiding Ethical AI Use

• Various international guidelines advocate for principles such as justice, transparency, autonomy protection, and ensuring technologies serve humanity's best interests—these are crucial when integrating AI into education systems.

• The synthesis presented in the discussed book aims to integrate these principles into an educational framework while addressing specific needs within academic environments.

Principles of Ethical AI in Education

Governance and Interdisciplinary Participation

• The first principle discussed is governance, emphasizing that institutions like UNAM must have agreed-upon normative mechanisms for overseeing AI use in education and research.

• It highlights the need for interdisciplinary participation to ensure ethical implementation throughout planning, monitoring, and evaluation phases.

Transparency and Accountability

• The second principle focuses on transparency, requiring AI technologies to explain their functioning clearly and allow for evaluations or audits to identify potential biases.

• Responsibility for the use of these systems lies with their providers, ensuring accountability in case of failures or issues.

Sustainability and Proportionality

• The third principle addresses sustainability, urging consideration of environmental impacts associated with AI systems while also managing technological dependencies on external suppliers.

• Proportionality is emphasized as a means to utilize AI judiciously for specific purposes that provide greater benefits than costs incurred.

Privacy and Data Management

• Privacy is highlighted as a crucial principle concerning personal data management, which must comply with existing regulations and be used solely for educational purposes when necessary.

• This includes measures to prevent unauthorized access or improper storage of sensitive information, particularly regarding minors.

Security and Inclusion

• The fifth principle stresses security; AI systems should be robust against attacks or misuse to avoid causing harm.

• Inclusion aims at reducing educational gaps by making AI accessible while preventing discrimination based on gender, socioeconomic status, or disabilities.

Human-Centric Approach

• The final principle asserts that AI should enhance rather than replace human roles in education—supporting autonomy, critical thinking capacity, and overall well-being while respecting fundamental human rights.

UNAM's Ethical Framework

Existing Institutional Ethics Code

• UNAM has an established ethics code since 2015 guiding institutional conduct encompassing principles such as peaceful coexistence, respect for diversity, equality, freedom of thought/expression.

Compatibility with International Standards

• Although not explicitly addressing technology-related issues currently, many principles within UNAM's ethics code align well with international standards proposed for ethical AI practices.

Importance of Academic Integrity

• A key excerpt from the ethics code emphasizes integrity and honesty as foundational values within academic activities—highlighting the importance of rigor in knowledge creation and transmission.

Ethics in Academic Work and Artificial Intelligence

Importance of Academic Integrity

• The significance of academic integrity is emphasized, highlighting the necessity to cite sources for ideas, texts, images, and other works used in university assignments.

• It is crucial to avoid falsifying or manipulating data, results, or information in academic work such as research projects and exams.

Ethical Guidelines and Regulations

• The current ethical code at UNAM serves as a general framework but may require further regulations specific to artificial intelligence contexts.

• Universities are encouraged to form their own ethics committees focused on research and teaching to implement these principles effectively.

Recommendations for Institutional Action

• A book referenced provides detailed approaches for integrating an institutional ethical framework that guides university teaching and research related to AI.

• The discussion transitions towards recommendations from Dr. Luis María Castañeda regarding the need for proactive engagement in constructing ethical frameworks within AI.

Addressing Current Challenges with AI

• Dr. Castañeda acknowledges the provocative nature of the topic and encourages participants to view recommendations as invitations for active involvement in ethical construction.

• Real-world examples illustrate how personal devices utilize AI algorithms based on user interactions, raising questions about data privacy and ethics.

Institutional Framework Development

• Recommendations are categorized into two main areas: institutional actions reinforcing normative frameworks through ethics committees representing the entire community.

• Emphasis is placed on understanding local contexts—Mexican universities' roles—and ongoing efforts over recent years toward defining ethical standards amid evolving technology.

Ongoing Discussions and Initiatives

• A permanent seminar on digital rights has been established to explore justice issues arising from AI usage within various societal roles.

• International seminars focus on discrimination linked with algorithmic biases, emphasizing the importance of addressing these challenges ethically.

Resources for Further Exploration

• Participants are invited to consult available materials related to AI's social sciences applications shared through university networks, promoting interdisciplinary dialogue around ethics.

Ethics in Action: Building Responsible AI

Community Engagement and Responsibility

• The speaker emphasizes the role of the university community in fostering discussions around ethical AI, encouraging participants to engage actively with a show of hands or hearts.

• There is a collective sense of responsibility among attendees to contribute towards creating an AI that enhances social well-being.

Access to Technology and Resources

• A key recommendation includes maintaining equitable access to technological infrastructure and resources, highlighting ongoing efforts to involve various institutions in this dialogue.

• The discussion aims at ensuring that all sectors can benefit from technological advancements without disparities.

Training and Interest in AI

• The speaker mentions a macro-training initiative on artificial intelligence, reflecting growing interest among students regarding its applications across diverse fields such as chemistry and social issues.

• There is an acknowledgment of the need for ethical discussions surrounding AI development, indicating that these conversations are still in their early stages.

Interdisciplinary Discussions and Protocol Development

• Institutional recommendations include promoting interdisciplinary discussions through seminars and workshops focused on AI's role in multilingual and multicultural contexts.

• Ethical protocols for graduate programs at UNAM have been developed to guide responsible use of AI technologies within academic settings.

Integration of AI into University Management

• Citing Dr. Sonia Venegas Álvarez, the speaker stresses that effective administrative systems should critically integrate AI while upholding ethical standards as core responsibilities.

• Forums for discussion have been established, including upcoming events like the International Congress on Administrative Law and Artificial Intelligence scheduled for 2025.

Educational Initiatives on Generative AI

• The importance of incorporating generative artificial intelligence into teaching practices is highlighted, advocating for critical usage rather than blind adoption.

• Various initiatives across faculties aim to promote ethical research practices involving AI, emphasizing transparency and critical engagement with technology.

Collaborative Efforts in Academic Research

• A significant collaborative effort led by Dr. Ana Yuri Ramírez has resulted in a repository consolidating academic work related to artificial intelligence at the university level, inviting further exploration by faculty members and students alike.

• This repository serves as a resource for accessing diverse research outputs concerning artificial intelligence applications across disciplines.

Call to Action

• The speaker concludes by urging participants to take active roles in building an ethical framework around AI development, reinforcing that it requires collective effort from everyone involved in academia.

Reflections on the Seminar

Overview of the Seminar Experience

• The speaker expresses gratitude for the seminar, highlighting its value and interaction among participants.

• Acknowledges that while there are divisions within the community, many recognize the potential of AI as a transformative tool in academia.

Insights on AI Usage

• Emphasizes the importance of responsible and critical use of institutional regulations regarding AI.

• Notes a demand for closer engagement in training and support related to AI initiatives presented by panelists.

Questions from Participants

• Marcela Heredia raises a question about differentiating between generative AI tools used by researchers, noting that 76% utilize these technologies.

Data on AI Production vs. Usage

• Dr. Yuri confirms that data exists regarding both production and usage of AI, stressing ethical considerations in model construction.

• Highlights the significance of clear datasets to ensure reliability and minimize bias in AI responses.

Ethical Considerations in AI Development

• Discusses ethical elements involved in constructing models, which apply not only to research but also to industry practices.

• Mentions international efforts to establish norms for identifying AI-generated content due to concerns over misinformation.

Regulatory Framework Discussion

• Addresses challenges with transparency in human communication about using AI technologies.

• Describes UNESCO's initiative aimed at ensuring identifiable markers within AI products to combat misuse or deception.

Recommendations for Normative Practices

• Suggests developing mechanisms that compel clarity around the use of AI technologies among users.

• Sonia Cruz asks about recommendations for regulatory frameworks at UNAM concerning ethical commissions addressing these issues.

Discussion on Ethical Use of AI in Academia

Overview of Institutional Guidelines

• The speaker emphasizes that the proposal should not be restrictive, referencing the university's existing ethical code which allows for a general normative framework.

• The university already has an applicable code of ethics, suggesting that while it may need some precision, it provides a foundation for addressing specific activities within academic areas.

Need for Specific Regulations

• There is potential for entities to create legislation or norms that directly support specific academic activities, indicating an evolution in guidelines due to advancements like AI.

• The speaker highlights the necessity for clear directives, using metaphors (e.g., "don't eat that apple") to illustrate the importance of explicit instructions regarding AI usage.

Professional Application and Responsibility

• It is suggested that universities should begin identifying opportunities where rules or criteria can guide students and faculty in their use of AI responsibly.

• The discussion points out the importance of having established rules so individuals know what actions are permissible or prohibited when using AI tools.

Principles Guiding Ethical Use

• Acknowledging foundational principles from over a century ago, the speaker stresses adherence to these principles when developing and utilizing AI technologies.

• Key values such as objectivity, honesty, and social responsibility are highlighted as essential components guiding ethical practices in academia concerning AI.

Conclusion and Future Directions

• The conversation wraps up by reiterating the significance of grounding discussions about AI in established ethical principles to ensure integrity in academic work.

• Participants are thanked for their engagement and reminded about future seminars focused on continuing education around these topics.