ΑΙhub.org
 

How to benefit from AI without losing your human self – a fireside chat from IEEE Computational Intelligence Society


by
02 December 2024



share this:

The image is a very detailed, black-and-white sketch-like illustration featuring a complex scene of interconnected figures and technology. The artwork portrays various individuals in different environments to represent the relationship between technology and humans. 

In the foreground, multiple people are surrounded by computer screens filled with data visualisations, charts, and technical information. A woman seated in an armchair appears deep in thought, surrounded by data-filled monitors. Beside her, a man leans over, using a tablet to assist with their inspection of a plant or tree. In the centre, a figure holds a large frame or screen displaying anatomical illustrations, representing the use of AI to analyse medical imagery. To the left, another person is intently observing a computer screen, while a second figure nearby is deeply immersed in analysing data. A woman dominates the right side of the composition, gazing upwards as if in contemplation or envisioning something beyond the immediate scene. The background features more people, including a family holding hands, and other abstract representations of data.Ariyana Ahmad & The Bigger Picture / Better Images of AI / AI is Everywhere / Licenced by CC-BY 4.0

In this fireside chat from IEEE Computational Intelligence Society, Tayo Obafemi-Ajayi (Missouri State University) asks Hava T. Siegelmann (University of Massachusetts, Amherst) about how to benefit from AI without losing your human self.

You can watch the chat in full below:




IEEE Computational Intelligence Society

            AUAI is supported by:



Subscribe to AIhub newsletter on substack



Related posts :

AI dives into a sea of data, from plankton to pollution

  16 Sep 2026
“Faster and cheaper monitoring means problems like plankton decline, litter accumulation, oil spills and coral degradation can be picked up and acted on sooner."

Interview with Yash Saxena: how is external knowledge used in AI systems?

  15 Sep 2026
What happens to information from external sources as it moves through an AI system?

When AI art has no author: Study finds generated images often can’t be traced to training data

  14 Sep 2026
A new method for surgically removing training examples from a model reveals that as datasets grow, the link between what a model learns and what it produces dissolves.

AI in nature conservation: powerful tool or dangerous shortcut?

  11 Sep 2026
AI provides opportunity for future biodiversity conservation but introduces risks .

Improving the process for large-scale recommender systems: an interview with Haruka Kiyohara

  10 Sep 2026
Credit-assigned policy gradient for early stage retrieval in two-stage ranking.

The Machine Ethics podcast: Data Collective with E.M. Lewis-Jong

Ben chats to E.M. Lewis-Jong about the promise of AI and making human connection easier, speech recognition and supporting linguistic diversity, making useful technologies that have a purpose, and more.

AI for ethology: an interview with Isla Duporge

  08 Sep 2026
Deep learning is becoming a powerful tool for understanding animal behaviour and tracking populations.

AI in cardiology: The path to practical application carries risks

  07 Sep 2026
Can artificial intelligence help us better combat cardiovascular diseases? Legal researcher Hannah van Kolfschooten urges caution, as there are still many legal issues that need to be resolved.



AUAI is supported by:







Subscribe to AIhub newsletter on substack




 















©2026.05 - Association for the Understanding of Artificial Intelligence