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




            AIhub is supported by:



Related posts :



More than half of new articles on the internet are being written by AI

  31 Dec 2025
The line between human and machine authorship is blurring, particularly as it’s become increasingly difficult to tell whether something was written by a person or AI.
monthly digest

2025 digest of digests

  30 Dec 2025
We look back through the archives of our monthly digests to pick out some highlights from the year.
monthly digest

AIhub monthly digest: December 2025 – studying bias in AI-based recruitment tools, an image dataset for ethical AI benchmarking, and end of year com

  29 Dec 2025
Welcome to our monthly digest, where you can catch up with AI research, events and news from the month past.

Half of UK novelists believe AI is likely to replace their work entirely

  24 Dec 2025
A new report asks literary creatives about their views on generative AI tools and LLM-authored books.

RL without TD learning

  23 Dec 2025
This post introduces a reinforcement learning algorithm based on a divide and conquer paradigm.

AIhub interview highlights 2025

  22 Dec 2025
Join us for a look back at some of the interviews we've conducted with members of the AI community.

Identifying patterns in insect scents using machine learning

  19 Dec 2025
Scientists will use machine learning to predict what types of molecules interact with insect olfactory receptors.

2025 AAAI / ACM SIGAI Doctoral Consortium interviews compilation

  18 Dec 2025
We collate our interviews with the 2025 cohort of doctoral consortium participants.



 

AIhub is supported by:






 












©2025.05 - Association for the Understanding of Artificial Intelligence