Youth, AI, and the Responsibility to Build Technology We Can Trust

The recording of the webinar is available here: https://www.pm4the.world/previousevents

Artificial intelligence is often discussed as though it were a distant force approaching from somewhere beyond us, but for young people in particular, it is already woven into daily life. It is present in classrooms, search engines, social media, entertainment, political communication, public services, and an expanding range of decisions that influence how people learn, work, communicate, and understand the world around them.

This reality formed the starting point of PM4TheWorld’s webinar, “Youth, AI, and the Responsibility to Build Technology We Can Trust,” featuring Long Nguyen, founder of Truth in Tech. Still a high school student, Long has already taken part in international policy conversations during the United Nations General Assembly High-Level Week and the United Nations Science, Technology and Innovation Forum. Through Truth in Tech, he is now working to help young people understand artificial intelligence not only as a set of tools, but as a social, political, and ethical force that they should have a role in shaping.

That distinction was central to the conversation. Young people are frequently described as the generation that will inherit the future, yet when governments, companies, schools, and institutions discuss the rules that should govern emerging technologies, youth are still too often treated as users to be educated, consumers to be protected, or populations to be studied. They are far less often recognized as legitimate participants in the governance of systems that are already affecting their education, privacy, civic engagement, mental well-being, and future employment.

Long’s own experience illustrates why this matters. When generative AI began moving rapidly into public life and education, he was still in middle school. Like many students, he witnessed the speed with which these tools became normalized, while teachers, school administrators, policymakers, and regulators were still trying to determine how they should be used, what risks they created, and what forms of oversight might be necessary.

Rather than focusing only on whether students should or should not use AI, he began asking broader questions. Who was responsible for the design of these systems? What data were they using? How were they being evaluated? What happened when they reproduced discrimination, generated misinformation, or enabled surveillance? Most importantly, why were the young people most directly exposed to these technologies rarely present in the discussions where such questions were being addressed?

Those concerns eventually led to the creation of Truth in Tech, a youth-led nonprofit initiative dedicated to promoting transparent, ethical, accountable, and human-centered technology governance. Its purpose is not to oppose innovation, nor to turn every young person into a software developer. Instead, it seeks to give students enough understanding to recognize how AI systems affect them, identify potential risks or bias, engage decision-makers, and advocate for more responsible approaches.

This is an important expansion of what AI literacy should mean. Learning how to use a tool, write a prompt, or generate content is no longer sufficient. Young people also need to understand how automated systems are trained, where bias may enter, how data can be collected and used, how digital rights may be affected, and where responsibility lies when a system causes harm.

Throughout the webinar, Long returned to the widening gap between technological development and institutional oversight. Artificial intelligence is advancing at a pace that local and national governments are struggling to match, while regulatory responsibility remains fragmented across agencies, jurisdictions, and legal frameworks that were often created before the current generation of technologies could have been imagined.

The result is a growing sense of uncertainty. AI can support education, improve access to information, accelerate research, strengthen environmental monitoring, and help organizations process complex problems. At the same time, it can enable intrusive surveillance, reproduce social inequalities, spread false information, generate deceptive content, and automate decisions in areas where people’s lives and opportunities are directly affected.

The challenge is therefore not to choose between innovation and regulation, as though one necessarily comes at the expense of the other. It is to ensure that innovation develops within a framework of responsibility, public accountability, and human rights.

Long described much of today’s AI development as taking place inside a “black box.” The public sees the products and experiences their consequences, but often has little visibility into the data used to train them, the standards applied to test them, the risks identified during development, or the safeguards established before deployment. People are increasingly asked to trust systems that they cannot fully understand and institutions whose internal processes remain largely hidden.

This is one of the reasons transparency emerged as such an important theme in the discussion. Yet the conversation also recognized that transparency cannot be treated as a simple or absolute solution. Greater openness may strengthen accountability, but it can also expose security vulnerabilities or proprietary information. Broader access may reduce inequality while simultaneously increasing opportunities for misuse. Regulation may protect people, but poorly designed rules can restrict legitimate freedom or prevent useful innovation.

Responsible governance therefore requires judgment rather than slogans. It requires institutions to recognize that transparency, privacy, security, access, innovation, and freedom may sometimes conflict, and that these tensions must be addressed through open processes, meaningful participation, and continuous review.

For Long, this is why local knowledge and ongoing feedback matter so much. A governance framework cannot be established once and assumed to remain appropriate indefinitely. Technologies evolve, their uses change, and their effects vary across communities. A system that appears acceptable in one setting may produce very different consequences elsewhere.

Governance must therefore remain connected to the people affected by technology. Young people, educators, community organizations, civil society groups, independent experts, policymakers, and companies all have a role in assessing whether a system is actually producing the outcomes it claims to deliver. This makes governance less a one-time decision than a continuing process of listening, reviewing, adapting, and correcting.

One of Truth in Tech’s most significant contributions is its TRANSPARENT Framework, an eleven-part methodology designed to make these issues more accessible to young people. Rather than asking students to master every technical detail, it gives them a language through which to examine AI systems and participate more confidently in discussions that might otherwise seem beyond their reach.

The framework begins with truth and integrity, encouraging young people to understand how a system is trained, deployed, and used. It then moves through representation, access, networks, safeguards, precision, accountability, resilience, equity, innovation, and trust. Together, these principles emphasize that responsible AI is not only about technical performance, but also about who is included, who is protected, who has access, who benefits, and who remains accountable.

The framework is intentionally broad because it is designed to work across different national and local contexts. Its value lies not in providing a single answer to every governance challenge, but in helping young people ask more informed questions and connect ethical principles to practical action.

That connection between awareness and action was another recurring theme of the webinar. Public discussions about AI often remain at the level of concern. People recognize that bias exists, acknowledge that privacy matters, and express anxiety about misinformation, surveillance, or harmful content, but the conversation frequently ends before anyone determines what should happen next.

Truth in Tech’s AI Action Plan seeks to move beyond that point by guiding young people through a structured process. The first step is to map the system: to define what it does, where it is used, who designed it, who authorized its deployment, what data it collects, where human judgment remains involved, and who may be affected if something goes wrong.

The next step is to assess impact by speaking with users and affected communities, gathering evidence, and identifying whether outcomes differ across groups. From there, participants are encouraged to identify gaps in oversight and propose practical solutions, whether through stronger human review, limits on data collection, independent auditing, clearer policies, changes in design, or new accountability mechanisms.

The final stage is advocacy. A well-developed proposal has little effect if it never reaches someone with the authority to act on it, so young people also need to understand how to engage teachers, school leaders, businesses, regulators, elected officials, and community organizations.

This is where AI education becomes a form of civic participation. Students are not simply learning about a technology; they are learning how to understand a system, document a problem, develop a response, and engage those responsible for making decisions.

The question of responsibility became particularly important during the discussion that followed Long’s presentation. When an AI system discriminates, enables surveillance, spreads false information, or contributes to a harmful decision, accountability can quickly become diffuse. Responsibility may sit partly with the developer, the company that sold the system, the institution that deployed it, the regulator that failed to intervene, or the individual who relied on its output.

In practice, responsibility may be shared, but it cannot be allowed to disappear.

Long argued that companies developing and deploying these technologies must be more transparent and should subject their systems to regular, independent assessment. Bias audits and third-party reviews should not be exceptional responses introduced only after public controversy; they should become part of responsible development and deployment.

Governments also have a responsibility to establish enforceable protections, particularly in areas such as privacy, biometric data, surveillance, and discrimination. At the same time, institutions using AI cannot treat the technology as an independent decision-maker and then distance themselves from the consequences.

A company cannot claim that an employment decision was neutral simply because software produced it. A school cannot rely on an automated system for a consequential judgment and then treat the outcome as beyond human review. A public agency cannot use an algorithm while refusing to explain how affected individuals can challenge its conclusions.

Technology may inform decisions, but it cannot assume moral responsibility for them. Algorithms do not hold fiduciary duties, explain moral choices, answer to communities, or repair harm. Human beings and institutions remain accountable for the systems they choose to create, purchase, and use.

The webinar also touched on the relationship between artificial intelligence, mental well-being, harmful content, screen exposure, and anxiety among younger users. These issues are especially difficult because AI is not entering young people’s lives through one isolated channel. It is increasingly embedded across education, entertainment, social interaction, and communication.

Limiting exposure may sometimes be appropriate, particularly for younger children, but avoidance alone will not prepare young people for the environment in which they are already living. Education must therefore begin before harm occurs.

Young people need to understand how synthetic content is produced, why an AI-generated answer may be inaccurate, how bias enters automated systems, and why some forms of personal information should not be shared. They also need to know what to do when they encounter something harmful, how to document a problem, who to inform, what rights they have, and where accountability sits.

These are not only technical questions. They belong to ethics, citizenship, education, leadership, and human rights. The technologies themselves will continue to change, but the principles needed to govern them—privacy, fairness, truth, accountability, dignity, and responsibility—are far more durable.

Society failed to prepare young people adequately for many of the consequences of social media. Artificial intelligence offers an opportunity, and an obligation, not to repeat the same mistake.

One of the clearest conclusions of the webinar was that trust cannot be treated as an additional feature to be attached to a system after development is complete. It must be built from the beginning through the assumptions made during design, the communities consulted, the data selected, the risks identified, the safeguards established, and the mechanisms created for review and correction.

Trust does not require believing that a system will never fail. It requires confidence that those responsible for it have taken reasonable steps to prevent harm, that they will be transparent when problems occur, and that affected people have a meaningful way to seek explanation and remedy.

This makes responsible AI a collective endeavor. Technology companies, governments, schools, universities, businesses, nonprofit organizations, civil society groups, project leaders, and organizational decision-makers all carry part of the responsibility. Young people must also be given genuine opportunities to participate, not because they should be expected to solve problems created by institutions, but because no governance system can credibly claim to represent the future while excluding those who will live in it the longest.

Long Nguyen’s work offers a compelling example of what youth participation can become when it is supported by education, structure, networks, and access to decision-makers. Through international events, educational initiatives, hackathons, partnerships, and policy discussions, Truth in Tech has already engaged thousands of students and created pathways through which young people can move from concern to informed action.

The significance of that work lies not only in the number of students reached, but in the model it represents. Young people are being encouraged to see themselves not as passive recipients of technological change, but as people with the right and capacity to question systems, understand their consequences, and participate in shaping better alternatives.

This reflects the broader mission of PM4TheWorld. The challenges created by artificial intelligence will not be addressed through declarations or good intentions alone. They require people who can translate concern into analysis, analysis into proposals, and proposals into responsible and sustainable action.

The future of AI should not be determined solely by those with the greatest technical capacity, financial resources, or institutional authority. It must also include the people whose lives will be shaped by the decisions being made today.

Young people are not waiting outside the technological future. They are already living within it, and the responsibility of institutions is not simply to prepare them for what is coming, but to give them a meaningful role in building it.

Continue the Conversation

Building technology we can trust will require sustained participation from educators, policymakers, technology professionals, nonprofit organizations, community leaders, parents, and young people themselves.

PM4TheWorld invites readers to watch the full webinar recording, explore the work of Truth in Tech, and consider what meaningful youth participation could look like within their own schools, organizations, institutions, and communities.

That reflection may begin with a few practical questions: Which AI systems are already affecting the people you serve? How transparent are those systems? Who is accountable when they cause harm? How are young people currently included in the decisions surrounding them? And what concrete action could be taken now to ensure that trust, responsibility, and human dignity are built into technology from the beginning?

The future of artificial intelligence is not predetermined. It is being shaped through the choices institutions and individuals make today, and those choices should include the voices of the generation that will live with them the longest.