Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Irina Mirkina, AI Lead, Office of Innovation, UNICEF, her thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

One of the main challenges is the complexity of AI development across borders and across the global value chains. Data collected in one country may be used, labelled, processed in other countries - and it's hard to ensure the data privacy and ethical AI development if AI laws in all those countries are different. Many extremely popular products (including generative AI systems) have been accused of disregarding human rights. Examples include using digital sweatshops with poor working conditions for data labelling and violating the creators' right to work. If such questionable practices happen at one end of a global value chain while the value is extracted at the other end, regulating AI on a global scale becomes extremely challenging.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Annelore Verhagen, Economist, Organisation for Economic Co-operation and Development, her thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

Ensuring responsible and ethical AI deployment requires a framework for how to work with AI, complemented by concrete, actionable and enforceable implementation plans. One of the critical challenges in this context is the risk of a fragmentation of efforts, which could unnecessarily harm innovation and create regulatory gaps. Fostering international collaboration is essential for mitigating this challenge effectively.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Andreea Munteanu, Product Manager, Canonical, her thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

AI world needs to better define guidance on how to build AI projects that are ethical and responsible. Also, the community could explore more the option of enabling sustainable AI.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Giovanni Leoni, Head of Business Strategy & Development, Credo AI, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

One of the most critical challenges that the AI community needs to address is the delicate balance between promoting the adoption of AI technology while ensuring responsible and ethical AI deployment. It’s not EITHER/OR type of situation, but rather an AND!

Our focus should be on designing AI systems, from their inception to deployment and ongoing monitoring, with responsible and ethical considerations at the forefront. This means that responsible and ethical AI should not be an afterthought but rather woven into the very fabric of AI development and implementation.

Achieving this balance is vital for the long-term sustainability and positive impact of AI on society.
Furthermore, enabling AI adoption according to the ambition of responsible and ethical coming through regulations, such as the EU AI Act is critical. Even more now, with the EU AI Act just around the corner, this spans more than just compliance, but also a matter of operationalizing ethical and responsible AI at scale in line with the high-level expert groups' guidelines on trustworthy AI.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Sako Arts, CTO And Co-founder, FruitPunch AI, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

Yes we need to focus on training the Engineers in such a way that they take partial responsibility. They need to know what impact their work can make and look for positions where this is done ethically, starving out those companies that don't due to a lack of engineers.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Christian Martinez, Finance Analytics Manager at Kraft Heinz, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

Explicability and Explainability.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Maciej Mazur, Principal ML Engineer at Canonical, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

I think the main challenge would be explainability. But not only on a traditional level, when we do it for legal reasons, but also ie. an LLM backed voice assistant explaining the user how it came to a certain conclusion.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Khagesh Batra, Head of Data Science, The Adecco Group, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & and ethical AI deployment?

- Data Bias: AI systems can inherit the biases present in their training data. This is problematic when these systems are used for decision-making in critical areas like criminal justice, healthcare, and employment.

- Algorithmic Fairness: Even if training data is balanced and unbiased, the algorithms themselves can introduce bias. Methods for auditing and mitigating algorithmic biases are crucial.

- Explainability: Many advanced AI models, including deep neural networks, are often considered "black boxes" because their operations are not easily interpretable by humans. A lack of explainability can be a serious issue when deploying AI in sensitive areas.

- Audit Trails: There needs to be a reliable way to audit decisions made by AI systems. This is particularly important for systems that might be involved in legal , finance and medical decisions.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Héctor López Romero, Bigdata & AI Senior Product Manager at Open Telekom Cloud, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & ethical AI deployment?

The big challenge is to include all stakeholders to the same ethical level that everyone knows and follows ethics at any level of implementation.

Ahead of World Summit AI (11th-12th October 2023, Taets Art & Event Park, Amsterdam), we asked Ferenc Kukucska, Bigdata & AI Architect, Open Telekom Cloud, his thoughts on the future of AI.

As an expert in the field, what critical challenges do you believe the AI community needs to address to ensure responsible & ethical AI deployment?

We need to explain to the users of the AI what exactly they are using, what data we used for training so 100% transparency and informing the end user are the most important things to do in my opinion