ICTO2024 PROGRAM

DOWNLOAD Program

Conference Partners

EMLV - Ecole de Commerce et de Management à Paris.png

École supérieure d'ingénieurs Léonard-de-Vinci — Wikipédia.png

HOSTS

De Vinci Research Center (DVRC)
EMLV Business School
ESILV Engireering School
IIM Digital School

CONFERENCE THEME

The ICTO2024 conference centers on "Augmented Intelligence for Smarter Societies," highlighting the partnership between human cognition and artificial intelligence (AI) to refine organizational decision-making. This theme reflects a significant shift from viewing AI as a substitute for human intelligence to a complementary force that enhances human capabilities (Harfouche, Quinio, Saba, & Saba, 2023), As outlined by Harfouche, Quinio, & Bugiotti (2023), there's a growing trend in organizations towards collaborative decision-making models that integrate the strengths of both humans and AI, fostering more effective and informed outcomes (Johnson, AlBizri, Harfouche, & Fosso-Wamba, 2022).

Augmented Intelligence is spotlighted for its role in elevating human decision-making, with a focus on models like that proposed by Shrestha et al. (2019), which detail how AI can support rather than supplant human knowledge. The advancement in Human-Centric Informed AI, as discussed by Harfouche, Quinio, Saba, & Saba, (2023), emphasizes a bidirectional interaction between AI systems and users, ensuring AI's decisions are made with a broad spectrum of data and are transparent and understandable to humans.

However, the journey towards fully realizing the potential of Explainable AI (XAI) is fraught with challenges (Johnson, AlBizri, Harfouche, & Tutun, 2023), including balancing complexity with interpretability and ensuring ethical alignment. Future pathways might involve creating Responsible AI frameworks and incorporating insights from psychology and social sciences to develop AI systems that are truly aligned with human needs and values (Tutun, Harfouche, Albizri, Johnson & Haiyue, 2022; Johnson, AlBizri, and Harfouche, 2021).

The conference aims to explore cutting-edge Augmented Intelligence applications, discuss its ethical and social implications, and promote interdisciplinary collaboration. Moreover, it will highlight the importance of Responsible AI in addressing biases and ensuring AI systems are ethically sound and enhance societal well-being.

Contributions are invited to share insights and research findings on Augmented Intelligence, aiming to foster the development of societies that are not only smarter but also more responsive to human needs. Through this collaborative exploration, the ICTO2024 conference seeks to chart a future where AI and human intelligence together drive societal progress.

REFERENCES

Harfouche, A., Quinio, B., Saba, M., & Saba, P. (2023). « The Recursive Theory of Knowledge Augmentation: Integrating human intuition and knowledge in Artificial Intelligence to augment organizational knowledge », Information Systems Frontiers, 25(1), 55–70.

https://doi.org/10.1007/s10796-022-10352-8

Harfouche, A., Quinio, B., & Bugiotti, F. (2023). « Human-Centric AI to Mitigate AI Biases: The Advent of Augmented Intelligence », Journal of Global Information Management (JGIM), 31 (5), 1-23

https://hal.science/hal-04263509/document

Johnson, M., AlBizri, A., Harfouche A., & Fosso-Wamba, S., (2022). « Integrating Human Domain Knowledge into Artificial Intelligence: Informed Artificial Intelligence ». International Journal of Information Management, 64. 102479.

https://doi.org/10.1016/j.ijinfomgt.2022.102479

Shrestha, Y. R., Ben-Menahem, S. M., & Von Krogh, G. (2019). « Organizational decision-making structures in the age of artificial intelligence ». California Management Review, 61(4), 66-83.

Johnson, M., AlBizri, A., Harfouche, A., & Tutun, S., (2023). « Digital Transformation to Mitigate Emergency Situations: Increasing Opioid Overdose Survival Rates through Explainable Artificial Intelligence », Industrial Management & Data Systems, 123(1), 324-344.

https://doi.org/10.1108/IMDS-04-2021-0248

Johnson, M., AlBizri, A. and Harfouche, A. (2023). « Responsible Artificial Intelligence in Healthcare: Predicting and Preventing Insurance Claim Denials for Economic and Social Wellbeing », Information Systems Frontiers, 25(6), 2179-2195.

https://doi.org/10.1007/s10796-021-10137-5

Tutun S., Harfouche, A., Albizri, A., Johnson M., & Haiyue, H. (2023). « A Responsible AI Framework to Mitigate the Ramifications of Organ Donation Crisis », Information Systems Frontiers, 25(6), 2301-2316.

https://doi.org/10.1007/s10796-022-10340-y