Laurentian University

I believe that like any technology humans have developed in the past , the ethical use of AI is also paramount. This means agreeing on how to develop, train and use it responsibly, covering social, environmental, cultural, linguistic and technical dimensions. That agreement must come first. Secondly a genuine long-term commitment from the world's most powerful leaders to prevent AI from being exploited for power or profit is essential. Lastly, public education on AI as it becoming more available and complex, matters just as much. These three things together: agreement, commitment and education, are what we need to focus on right now.

• Safe, secure and trustworthy AI
• Social, economic, ethical, cultural, linguistic and technical implications of AI
• Transparency, accountability, and human oversight
• AI capacity-building

Safe, Secure and Trustworthy AI We have already witnessed numerous incidents of discrimination. With the misuse of technology, intentional or not, the same patterns will only be amplified with AI. From personal data to child safety, vulnerable populations and institutional knowledge, all of it needs attention. AI Capacity Building I see this from two angles. First, training AI itself. What it is being fed, how it processes that information and whether it informs or misinforms humans. Second, building human capacity, both professionally and personally, to understand the risks and make the best use of AI. Social, Economic, Ethical, Cultural, Linguistic and Technical Implications There are many. As I mentioned earlier, AI development has so far been largely driven by a narrow demographic. With this this pace, it risks amplifying already existing discrimination and widening the gap between rich and poor. Especially within organisations gaps across roles, departments and locations could deepen further if people are not properly trained. Transparency, Accountability and Human Oversight We are all trying to uncover the AI black box and understand how it shapes decisions, often leaving users unaware of how much they are being influenced by machines. Until that changes, fully relying on machine decisions is not realistic. There is still a long way to go before reaching human intelligence, let alone human instinct. Human oversight is without doubt essential.

I think all points are largely covered but as it is a developing field and being developed and used also most simultaneously, there will be new concerns as we move along. I believe human AI integration and symbiosis is an important factor that should be discussed separately. Its not training, not oversight, not controlling but augmenting decision with the right mix of human discretion and AI processing.

As mentioned earlier AI is itself in a development stage an no one get has been able to for see what lies in future hence every step that we take as developers profit makers users Regulators or any other roles is equally important and must be closely monitored at all times. This awareness helps us to keep check of what we are developing how we are using and what improvements I needed to prevent any unwanted outcomes that affect a large population. Hence significant challenges include: Continuous monitoring of all phases of AI Making it accessible to everyone without discrimination but also checking the environmental impacts that AI brings Balancing free usage for educational and developmental purposes rather than content specially on social media that increases violence discrimination misinformation Using AI in replacing jobs that are precarious and dangerous for humans but having a limit of what is replaced and how we are going to manage joblessness Checking the use of AI in educational sector to ensure that the human intelligence is nowhere at stake Increased use of AI robotics in care economy where the world is already facing a labour deficit All the other challenges automatically convert themselves into opportunities as getting ahead of these challenges itself is a lot of work.