Roundtable insights from ICAI Day: AI Impact for Tomorrow

Roundtable insights from ICAI Day: AI Impact for Tomorrow

June 13, 2024
Written by
Community Manager

On the 5 June we hosted together with Erasmus University Rotterdam and Erasmus Centre for Data Analytics, our ICAI Day Spring Edition on the topic of 'AI Impact for Tomorrow'. This event was a vibrant platform for discussing how future AI technologies can be harnessed to not only drive advancements in the field but also to ensure these developments positively impact society. This ICAI Day underscored the vital role of collaborative efforts, bringing together academia, industry, and government to craft a future where AI acts as a catalyst for good, propelling us towards a more sustainable, equitable, and interconnected world.

During the ICAI day we hosted Roundtables. These led to passionate discussions on the following topics: Green AI: Sustainable Computing and Efficiency, From Collaboration to Impact: Realising the Potential of AI Partnerships, Fostering AI Talent for an Unknown Future, AI for Sustainable Energy: Accelerating the Transition to Renewables, and finally Building Bridges: Fostering Inclusive AI.

Here are the key takeaways from the discussions:

Green AI: Sustainable Computing and Efficiency

Hosted by June Sallou (Postdoc Researcher at TU Delft) and Helena Samodurova (co-founder at Incooling).

  1. Academia-Industry Collaboration: Green AI research in academia needs better transfer to industry. Efforts should enhance communication and knowledge transfer to implement sustainable AI practices in businesses.
  2. Awareness: Raising awareness about AI's environmental impact is crucial. Actions include using standards and metrics, investing in education, and integrating sustainability into company cultures.
  3. Regulation: Regulations on the environmental impact of AI applications are necessary. This could involve limiting energy usage by companies while considering inclusivity and equity.
  4. Upskilling: Organizations should start with small AI trials and expand gradually to improve skills.
  5. Realistic Use: AI is often overhyped but underutilized in practical applications.

From Collaboration to Impact: Realising the Potential of AI Partnerships

Hosted by Mirjam Plantinga (Associate Professor at UMCG) and Bob Huisman (Research & Development Manager at NS).

  1. Common Goal: Effective collaboration requires agreement on common goals, respect for diverse perspectives, and clear roles and responsibilities.
  2. Market Translation: Specific expertise and responsibility from the start of collaborations are necessary to translate AI research into market impact.
  3. Selective Investment: Avoid investing in solutions that do not address the problem, are irresponsible, or are not feasible or scalable.
  4. Collaboration as a Vehicle: Collaboration is key to reaching a common goal and realizing the potential of AI partnerships.

Fostering AI Talent for an Unknown Future

Hosted by Morraya Benhammou (Lecturer at HHs, AI mentor at TechLabs) and Stijn van der Krogt (Dean at AMSIB). 

  1. Embrace Change: Being adaptable and ready for change is essential to maximize benefits and minimize risks in the uncertain future of AI.
  2. Skill Generation: Focus on generating skills rather than just knowledge to prepare future AI talent.
  3. Transparency: Increased transparency from the industry on real gaps in AI talent is needed for practical impact.
  4. Essential Skills: Developing soft skills, resilience, empathy, and the ability to deal with change is crucial for embracing AI-related changes.
  5. Current Limitations: Understanding current limitations of AI while being aware of its potential future impacts is vital.

AI for Sustainable Energy: Accelerating the Transition to Renewables

Hosted by Malou Kroezen (Director at ECET) and Sarah Craig (Director at ECET).

  1. Optimizing Energy Consumption: AI can optimize energy consumption and influence consumer behavior to support a sustainable energy transition.
  2. Bottlenecks: Trust in data sharing, data privacy, and lack of AI literacy and talent are significant challenges.
  3. Responsibility: Identifying responsibility within the quadruple helix (government, society, academia, industry) and understanding AI's impact is essential.
  4. Technology vs. Social Innovation: Discussing whether technology innovation enhances social innovation or vice versa is important for understanding AI's role.

Building Bridges: Fostering Inclusive AI

Hosted by Gabriele Jacobs (Professor at EUR) and Cristina Zaga (Assistant Professor at UT).

  1. Inclusivity Confusion: There is confusion about the meaning of inclusive AI, with diverse interpretations ranging from diversity to practical guidelines.
  2. Guidelines Issue: Checklists and responsible AI guidelines are often seen as confusing and impractical, leading to a preference for post-development inclusivity efforts.
  3. Support for PhD Students: PhD students need more support in learning about social justice and inclusivity, which are often missing in their programs.
  4. Challenging the Status Quo: Using AI to challenge the status quo is important, and nurturing spaces for such discussions aligns with current literature.
  5. Literacy on Inclusivity: There is a dire need for increased literacy about inclusivity and moving beyond buzzwords.

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