Discover a whole new take on Artificial Intelligence with Squirro's educational podcast! Join host Lauren Hawker Zafer, a top voice in Artificial Intelligence on LinkedIn, for insightful chats that unravel the fascinating world of tech innovation, use case exploration and AI knowledge. Dive into candid discussions with accomplished industry experts and established academics. With each episode, you'll expand your grasp of cutting-edge technologies and their incredible impact on society, and y ...
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Transforming Recruitment with AI: Surveys, Sentiment, and Data-Driven Insights - ML 161
MP3•Episoder hjem
Manage episode 433399347 series 2977446
Innhold levert av Charles M Wood. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Charles M Wood eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
In today's episode, our hosts Michael, Ben, and special guest Keith Goode delve deep into the transformative role of AI and machine learning in modern HR practices. They tackle a range of topics, starting with the innovative use of AI to streamline surveying and sentiment analysis in employee evaluations. They explore the exciting potential of AI models in technical data collection, particularly for interviews, and discuss how these models can assess candidates' sentiment and confidence levels, providing valuable insights into their fit for specific roles.
They also hear about the emerging trends discussed at the recent Databricks Data and AI Summit, where generative AI for resume screening took center stage. They debate the challenges and opportunities of leveraging AI to reduce information overload in analytics, particularly within the complex hiring process. They emphasize the importance of explainable AI models, consulting scalability, and the perennial issue of data cleansing in HR.
Additionally, the episode touches on the critical aspects of diversity and inclusion in the workplace, the influence of new legislation on workforce diversity modeling, and how companies can configure HR systems to suit their unique needs. They share insights into using advanced tools like XGBoost for predictive modeling, highlight the significance of face-to-face interactions in interview processes, and caution against over-reliance on automated resume screening.
Join them as they navigate these thought-provoking discussions and more, shedding light on the intersection of AI, machine learning, and human resources.
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
continue reading
They also hear about the emerging trends discussed at the recent Databricks Data and AI Summit, where generative AI for resume screening took center stage. They debate the challenges and opportunities of leveraging AI to reduce information overload in analytics, particularly within the complex hiring process. They emphasize the importance of explainable AI models, consulting scalability, and the perennial issue of data cleansing in HR.
Additionally, the episode touches on the critical aspects of diversity and inclusion in the workplace, the influence of new legislation on workforce diversity modeling, and how companies can configure HR systems to suit their unique needs. They share insights into using advanced tools like XGBoost for predictive modeling, highlight the significance of face-to-face interactions in interview processes, and caution against over-reliance on automated resume screening.
Join them as they navigate these thought-provoking discussions and more, shedding light on the intersection of AI, machine learning, and human resources.
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
188 episoder
MP3•Episoder hjem
Manage episode 433399347 series 2977446
Innhold levert av Charles M Wood. Alt podcastinnhold, inkludert episoder, grafikk og podcastbeskrivelser, lastes opp og leveres direkte av Charles M Wood eller deres podcastplattformpartner. Hvis du tror at noen bruker det opphavsrettsbeskyttede verket ditt uten din tillatelse, kan du følge prosessen skissert her https://no.player.fm/legal.
In today's episode, our hosts Michael, Ben, and special guest Keith Goode delve deep into the transformative role of AI and machine learning in modern HR practices. They tackle a range of topics, starting with the innovative use of AI to streamline surveying and sentiment analysis in employee evaluations. They explore the exciting potential of AI models in technical data collection, particularly for interviews, and discuss how these models can assess candidates' sentiment and confidence levels, providing valuable insights into their fit for specific roles.
They also hear about the emerging trends discussed at the recent Databricks Data and AI Summit, where generative AI for resume screening took center stage. They debate the challenges and opportunities of leveraging AI to reduce information overload in analytics, particularly within the complex hiring process. They emphasize the importance of explainable AI models, consulting scalability, and the perennial issue of data cleansing in HR.
Additionally, the episode touches on the critical aspects of diversity and inclusion in the workplace, the influence of new legislation on workforce diversity modeling, and how companies can configure HR systems to suit their unique needs. They share insights into using advanced tools like XGBoost for predictive modeling, highlight the significance of face-to-face interactions in interview processes, and caution against over-reliance on automated resume screening.
Join them as they navigate these thought-provoking discussions and more, shedding light on the intersection of AI, machine learning, and human resources.
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
…
continue reading
They also hear about the emerging trends discussed at the recent Databricks Data and AI Summit, where generative AI for resume screening took center stage. They debate the challenges and opportunities of leveraging AI to reduce information overload in analytics, particularly within the complex hiring process. They emphasize the importance of explainable AI models, consulting scalability, and the perennial issue of data cleansing in HR.
Additionally, the episode touches on the critical aspects of diversity and inclusion in the workplace, the influence of new legislation on workforce diversity modeling, and how companies can configure HR systems to suit their unique needs. They share insights into using advanced tools like XGBoost for predictive modeling, highlight the significance of face-to-face interactions in interview processes, and caution against over-reliance on automated resume screening.
Join them as they navigate these thought-provoking discussions and more, shedding light on the intersection of AI, machine learning, and human resources.
Socials
Become a supporter of this podcast: https://www.spreaker.com/podcast/adventures-in-machine-learning--6102041/support.
188 episoder
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