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How to deal with bias in Artificial Intelligence models?
๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ฐ๐ผ๐บ๐บ๐ผ๐ป ๐ฎ๐ป๐ฑ ๐๐ต๐ฎ๐ ๐ฑ๐ถ๐๐๐ถ๐ป๐ด๐๐ถ๐๐ต๐ฒ๐ ๐ฐ๐ฟ๐ฒ๐ฑ๐ถ๐ ๐ฟ๐ฎ๐ป๐ธ๐ถ๐ป๐ด๐ ๐ฎ๐ป๐ฑ ๐๐ต๐ฒ ๐ฐ๐ถ๐๐ ๐ผ๐ณ ๐๐บ๐๐๐ฒ๐ฟ๐ฑ๐ฎ๐บ ๐ถ๐ป ๐๐ฒ๐ฟ๐บ๐ ๐ผ๐ณ ๐ฑ๐ฒ๐ฎ๐น๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐๐ ๐ฎ๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐?
To talk about challenges in the domain of bias in AI, I invited fantastic guests:
Elsa Sklavounou , an expert on Natural Language Processing (NLP), a researcher in the area of linguistics and computational linguistics (Ph.D.), VP of AI Alliances, Global Partnerships - Content Technology at RWS Group,
Marijn Markus , AI Lead, data scientist, public speaker and thought leader, Managing Consultant at Capgemini,
Matt Fornito , AI transformation advisor to Fortune 500 companies, a keynote speaker and thought leader, Chief Data Officer at revenue.io
In the fifteenth episode of Sherpa Search on Tech, we discuss:
โ
What makes Artificial Intelligence biased? Data, algorithms or people?
โ
How can we bring inclusivity into artificial intelligence? How can we make AI more beneficial for society?
โ
A need to look at data collected from a different point of view to get a more holistic view
โ
What is bias and how do they arise?
โ
Are big data sets better for creating AI models?
โ
The role of data scientists in the decision-making process, and what model they need to apply.
โ
Do we really need tons of data collection?
โ
How can we deal with a diversity of data, and what actions do we need to take?
โ
What do we want to achieve with the use of AI, do we want AI to reproduce reality or rather teach us something?
โ
What is the real โscienceโ part of data science?
โ
Bias is everyoneโs problem because every company will be one day a data-driven business.
โ
Global and local perception of data and discrepancies between the US and Europa.
โ
Insights on regulating Artificial Intelligence.
โ
ChatGPT
โ
Book recommendations
I highly recommend this talk!
Links:ย
Maciej Szczerba on Linkedinย
ย Elsa Sklavounou on Linkedinย
Marijn Markus on Linkedin ย ย
Matt Fornito on Linkedinย
ย Listen to the episode and subscribe to Sherpa Search on Tech on your favourite platform: ย
๐ข Newsletter https://www.sherpasearch.tech/en/blog ย
๐ข YouTube https://youtu.be/jdXXvIhKWl8 ย
๐ข Spotifyย
๐ข Vimeo https://vimeo.com/790315238 ย
...ย
Sherpa Search is an executive search firm specializing in the tech industry, helping hire the right people and advising how to build and develop long-lasting high performing IT teams. We provide data-driven recruitment and assessment based on machine learning algorithms and McQuaig's renowned psychometric tools. ย SERVICES โคต๏ธ
โ ย Recruitment for expert-level and senior leadership positions, with a focus on AI/ML/Data Science experts, CTO, Big Data and Cloud experts across EMEA โ Data-driven recruitment and assessment, based on machine learning algorithms and McQuaig's renowned psychometric tools.
ย ย www.sherpasearch.tech
View all episodes
By Maciej Szczerba๐ช๐ต๐ฎ๐ ๐ถ๐ ๐ฐ๐ผ๐บ๐บ๐ผ๐ป ๐ฎ๐ป๐ฑ ๐๐ต๐ฎ๐ ๐ฑ๐ถ๐๐๐ถ๐ป๐ด๐๐ถ๐๐ต๐ฒ๐ ๐ฐ๐ฟ๐ฒ๐ฑ๐ถ๐ ๐ฟ๐ฎ๐ป๐ธ๐ถ๐ป๐ด๐ ๐ฎ๐ป๐ฑ ๐๐ต๐ฒ ๐ฐ๐ถ๐๐ ๐ผ๐ณ ๐๐บ๐๐๐ฒ๐ฟ๐ฑ๐ฎ๐บ ๐ถ๐ป ๐๐ฒ๐ฟ๐บ๐ ๐ผ๐ณ ๐ฑ๐ฒ๐ฎ๐น๐ถ๐ป๐ด ๐๐ถ๐๐ต ๐ฑ๐ฎ๐๐ฎ ๐ฎ๐ป๐ฑ ๐๐ ๐ฎ๐น๐ด๐ผ๐ฟ๐ถ๐๐ต๐บ๐?
To talk about challenges in the domain of bias in AI, I invited fantastic guests:
Elsa Sklavounou , an expert on Natural Language Processing (NLP), a researcher in the area of linguistics and computational linguistics (Ph.D.), VP of AI Alliances, Global Partnerships - Content Technology at RWS Group,
Marijn Markus , AI Lead, data scientist, public speaker and thought leader, Managing Consultant at Capgemini,
Matt Fornito , AI transformation advisor to Fortune 500 companies, a keynote speaker and thought leader, Chief Data Officer at revenue.io
In the fifteenth episode of Sherpa Search on Tech, we discuss:
โ
What makes Artificial Intelligence biased? Data, algorithms or people?
โ
How can we bring inclusivity into artificial intelligence? How can we make AI more beneficial for society?
โ
A need to look at data collected from a different point of view to get a more holistic view
โ
What is bias and how do they arise?
โ
Are big data sets better for creating AI models?
โ
The role of data scientists in the decision-making process, and what model they need to apply.
โ
Do we really need tons of data collection?
โ
How can we deal with a diversity of data, and what actions do we need to take?
โ
What do we want to achieve with the use of AI, do we want AI to reproduce reality or rather teach us something?
โ
What is the real โscienceโ part of data science?
โ
Bias is everyoneโs problem because every company will be one day a data-driven business.
โ
Global and local perception of data and discrepancies between the US and Europa.
โ
Insights on regulating Artificial Intelligence.
โ
ChatGPT
โ
Book recommendations
I highly recommend this talk!
Links:ย
Maciej Szczerba on Linkedinย
ย Elsa Sklavounou on Linkedinย
Marijn Markus on Linkedin ย ย
Matt Fornito on Linkedinย
ย Listen to the episode and subscribe to Sherpa Search on Tech on your favourite platform: ย
๐ข Newsletter https://www.sherpasearch.tech/en/blog ย
๐ข YouTube https://youtu.be/jdXXvIhKWl8 ย
๐ข Spotifyย
๐ข Vimeo https://vimeo.com/790315238 ย
...ย
Sherpa Search is an executive search firm specializing in the tech industry, helping hire the right people and advising how to build and develop long-lasting high performing IT teams. We provide data-driven recruitment and assessment based on machine learning algorithms and McQuaig's renowned psychometric tools. ย SERVICES โคต๏ธ
โ ย Recruitment for expert-level and senior leadership positions, with a focus on AI/ML/Data Science experts, CTO, Big Data and Cloud experts across EMEA โ Data-driven recruitment and assessment, based on machine learning algorithms and McQuaig's renowned psychometric tools.
ย ย www.sherpasearch.tech