Psych Tech @ Work Dr. Charles Handler

Quote:

We talk about the effect of technology on everything, but ultimately, it's the people that matter." This theme has shown up repeatedly, emphasizing that technology doesn't have uniform effects; we have to consider the psychology of implementation, how it's used, and its context​​.

Summary:

In a thought-provoking episode of "People, Science, Inc.," Dr. Charles Handler sits down with Dr. Tara Behrend, a leading expert in the intersection of industrial-organizational psychology and technology. They explore the profound impact of technology, especially AI, on workplace dynamics, employee well-being, and organizational effectiveness. Dr. Behrend, with her extensive background in the study of how technology influences human behavior at work, sheds light on critical issues such as the ethical use of AI in hiring, the psychological effects of remote work technologies, and the future of learning and development in increasingly digital environments.

In this engaging episode of "People, Science, Inc.," Dr. Charles Handler welcomes Dr. Tara Behrend, an esteemed Industrial and Organizational Psychologist and current president of SIOP. Dr. Behrend, also a professor at Michigan State University, shares her insights into the psychological implications of emerging technologies in the workplace, the role of AI in learning and connection, and the significance of career and technical education in addressing evolving workforce demands. With a focus on how AI and technology impact employee well-being, decision-making, and organizational dynamics, this conversation sheds light on the critical intersection of psychology, AI ethics, and workplace innovation.


Take aways:

Balancing AI and Ethics in Hiring: The discussion reveals that while AI can streamline the hiring process, it requires a careful balance to ensure ethical application. Dr. Behrend stresses the importance of transparency and continuous oversight in AI systems to mitigate biases and uphold fairness, providing a blueprint for organizations to follow.

Adapting to Remote Work Technologies: Insights from the episode illustrate that successful remote work depends not just on the technology used but on how it's implemented. Strategies for maintaining communication, fostering collaboration, and sustaining engagement in remote settings are crucial for preserving company culture and employee well-being.
Innovating Learning and Development: Dr. Behrend points out that technology's role in learning and development extends beyond access to information. It involves creating adaptive systems that tailor learning experiences to individual needs, promoting more effective skill acquisition and career growth.

Understanding the Psychological Impact of AI: One of the pivotal learnings is the nuanced psychological impact of AI on employees, including feelings of trust or mistrust towards automated systems. Companies are encouraged to foster an environment where technology serves as a support, not a replacement, enhancing job satisfaction and productivity.
Navigating Technological Change: The episode underlines the necessity for both organizations and employees to remain agile amidst technological advancements. This involves fostering a culture that values upskilling, reskilling, and continuous learning as essential components for thriving in the evolving workplace landscape.

Addressing Surveillance in the Workplace: Through her insights, Dr. Behrend highlights the increasing use of surveillance tools in monitoring employee productivity and behavior. A key learning from her work is the critical need for ethical guidelines and transparent communication about the use and purpose of surveillance technologies. Organizations must balance efficiency and privacy concerns, ensuring that surveillance practices are implemented with respect to employee autonomy and trust, thereby preventing...

"Legislation... has not kept up with the pace of technological advancements, posing significant challenges for ensuring fairness in AI-driven hiring processes."
-Matt Scherer
Summary:
In this episode of "Science 4-Hire,"  I welcome Matt Scherer, Senior Policy Counsel for Workers' Rights at the Center for Democracy in Technology, a non-profit based in Washington, D.C. The CDT champions the advancement of civil rights in the digital age, striving to ensure technology respects and enhances individuals' rights and democratic values.
Matt and I have an enthusiastic conversation about the importance of understanding and navigating the evolving landscape of AI and automation in hiring processes. 
Matt brings his expertise to the table, dissecting the intersection of emerging technologies with workplace rights, the nuances of AI legislation, and the vital role of public policy in safeguarding fairness and privacy. 
Matt and I dive right into some great dialogue about the challenges posed by electronic surveillance, automated management systems, and the quest to elevate worker voices through technology. 
We spend a good deal of time focusing on the critical evaluation of AI hiring tools, highlighting New York City's Local Law 144 and its implications for a broader regulatory framework. 
Matt provides some really interesting and important points about the criticality of using a design-first mentality in developing AI tools as a critical part of ensuring they serve to enhance worker empowerment rather than diminish it.

Insightful Moments:
Matt discusses the Center for Democracy in Technology's (CDT) mission to advance civil rights in the digital age, focusing on the workplace implications of emerging technologies such as AI and automated management systems. The CDT's commitment to this cause is grounded in ensuring technology serves to enhance, not undermine, workers' rights and privacy.
The conversation highlights New York City's Local Law 144, examining its strengths and weaknesses in regulating AI hiring tools. Despite being a pioneering piece of legislation, Matt suggests that the law is riddled with loopholes that many companies exploit to avoid compliance, demonstrating the challenges in crafting effective regulatory frameworks.
Matt emphasizes the importance of design-first thinking in developing AI technologies for hiring. He argues that most challenges associated with AI and automated hiring tools stem from design issues, advocating for a holistic approach that integrates ethical considerations from the outset.
The dialogue touches on the role of transparency in AI-driven hiring processes.  Current practices often leave candidates in the dark about when and how they are being evaluated by AI, stressing the need for legislation that mandates clear disclosure to candidates.
An exploration of upcoming legislation reveals a split between stronger regulatory regimes advocated by civil rights groups and more loophole-ridden proposals pushed by tech companies. This tension underscores the ongoing debate over how to effectively govern AI in hiring while protecting workers' rights.
Matt shares insights into the civil rights standards for 21st-century employment selection procedures, a document aimed at modernizing and expanding upon the 50-year-old uniform guidelines for employee selection procedures. This initiative reflects a broader effort to update legal and ethical standards for employment assessments in light of advancements in AI and technology.

In this episode of Science 4-Hire, I welcome my new friend Martyn Redstone, founder of pplbots and a pioneering force in the intersection of conversational AI and recruitment technology.

We have a fun and meaningful conversation about the evolution of chatbots and the role of generative AI in the recruitment process. With over two decades in technology and a laser focus on conversational AI solutions for recruitment, Martyn shares his journey through the advancement of chatbots from simplistic decision trees to complex systems empowered by natural language understanding, processing, and now, generative AI. 

We thoroughly explore the implications of chatbots and AI technology on candidate experience, the nuances of designing effective chatbot interactions, and the potential pitfalls and promises of leveraging large language models in recruitment. 

This conversation delves into the significant shifts in recruitment technologies, the criticality of design-first approaches, and the careful balance between innovation and ethical considerations in implementing AI tools. 


Quotes:

"Now, we're seeing the move to generative AI-based chatbots... but it always comes down to having a design-first mentality." 
-Martyn Redstone: 


Insightful Moments:


Evolution of Chatbots: Martyn illustrates the journey from basic chatbots to sophisticated systems enhanced by conversational AI and generative AI technologies, highlighting the transformative impact on the recruitment landscape.


Design Challenges: The conversation illuminates the complexities behind designing chatbot experiences that are not only technologically advanced but also ethically sound and user-friendly.


Generative AI in Recruitment: They discuss the advent of generative AI in recruitment, addressing both its potential to revolutionize candidate engagement and the inherent risks of relying too heavily on such models without adequate safeguards.


Practical Applications: Martyn shares insights into real-world applications of conversational AI in recruitment, from enhancing candidate screening to re-engaging talent pools through intelligent, automated interactions.

"This AI piece and all the ethics and governance and everything that goes around that... it really warrants a dedicated role and some specific communities focused on AI ethics and risks."

Bob Pulver: Founder of Cognitive Path


Summary:


My guest for this episode is Bob Pulver, a seasoned expert in the intersection of artificial intelligence and talent acquisition, bringing with him over two decades of experience from his tenure at IBM to the forefront of AI ethics and responsible implementation.


This episode not only provides valuable insights into the mechanics of implementing 
responsible AI, but also frames a narrative that reveals the complexity and necessity of ethical AI practices in today's technology-driven hiring landscape.


Bob underscores the importance of ethical AI development, emphasizing responsibility by design, speaking to the need for a proactive stance in integrating AI into people practices.  We both agree that compliance should not be a band-aid, or afterthought, but a foundational principle that begins with data acquisition and continues through to the implementation of AI-powered tools. 


A big part of our conversation revolves around legislation related to the use of AI hiring tools, including New York City's Local Law 144. Bob provides advice to organizations on navigating its anti-bias legislation and the broader implications for global regulatory landscapes.


In sum, Bob and I both agree that responsible AI is not a game of short sighted interventions, but rather a transformative shift that affects every aspect of talent acquisition. We provide our ideas on how to navigate through this period of intense change, focusing on the practical challenges companies face, from internal upskilling to grappling with legislation that struggles to keep pace with technological advancements.


Takeaways:

Start with a Foundation of Ethics and Responsibility: Implementing responsible AI requires building your technology on a foundation of ethical considerations. This involves considering the impact on protected groups, ensuring accessibility, and integrating privacy and cybersecurity measures from the beginning.Understand and Comply with Relevant Legislation: Staying informed about and compliant with anti-bias legislation, like New York City's Local Law 144, is crucial. This law requires annual independent audits for automated employment decision tools, ensuring they don't adversely impact protected classes.Adopt a Holistic Approach to AI Implementation: Responsible AI transcends legal compliance to include a broader ethical framework. It encompasses fairness, privacy, cybersecurity, and the mitigation of various risks, including reputational, financial, and legal.Engage in Continuous Education and Upskilling: All stakeholders, regardless of their role, need to be educated about the ethical implications of AI. This includes understanding how to acquire and test data to mitigate bias and ensure the responsible use of AI technologies.Foster a Multi-Stakeholder, Cross-Disciplinary Dialogue: Creating solutions that are both innovative and responsible requires input from a diverse group of stakeholders. This includes technical experts, ethicists, legal teams, and end-users to ensure cognitive diversity and address the ethical, cultural, and practical aspects of AI.
Prepare for an AI-Driven Transformation: Recognizing that AI transformation affects every aspect of an organization is essential. This realization should drive a commitment to responsible AI practices throughout the organization, from product development to...

“So most of the world is made up of full stack application developers who build software for anything from HRIS to accounting, to supply chain, and what have you? For those people to easily add generative AI capabilities into their applications while remaining in compliance with the security, trust, and safety requirements that enterprises have, well that's a fairly difficult challenge.” Vivek Sriram- Co-founder of Bookend.ai

Summary: In this episode of Science 4-Hire, I welcome my old friend and partner in crime Vivek Sriram, co-founder of Bookend AI, a start up that provides secure infrastructure that supports the efficient spin up and fine tuning of open source LLMs.

We waste no time delving into the fascinating, confusing, and intricate world of Large Language Models (LLMs) and their burgeoning role within enterprise solutions, with a special focus on HR and hiring applications. We sure do agree on the transformative potential of LLMs to revolutionize enterprise software, enhancing functionalities such as candidate screening, resume parsing, and even generating interview questions—tasks pivotal to modern HR departments.

Vivek brings me back down to earth a bit as he provides words of caution about the considerable challenges that come with integrating LLMs into enterprise systems, especially within the HR sector. Concerns around data privacy, the risk of perpetuating biases, and maintaining compliance with labor laws are significant when deploying AI in hiring. Vivek emphasizes the critical need for enterprises to navigate these challenges carefully, ensuring that LLM integration respects ethical guidelines and regulatory requirements, thus preventing potential adverse impacts on candidates and the hiring process.

The good news is that Vivek outlines strategies for implementing LLMs in a manner that balances innovation with responsibility. Approaches such as utilizing open-source models for greater control and customization, and employing platforms that offer secure, compliant AI integration, are discussed as viable solutions. The idea of fine-tuning LLMs with proprietary data to better align with specific HR needs provides additional levels of confidence for those looking to use LLMs securely.

Listeners will gain a nuanced understanding of the dual-edged nature of LLMs in HR and hiring contexts—recognizing their potential to significantly improve efficiency and decision-making in talent acquisition, while also grappling with the ethical, privacy, and compliance issues inherent in their use. This episode underscores the importance of thoughtful AI integration in HR practices, aiming for a future where technology serves to augment human judgment rather than supplant it.

Take Aways:
We must recognize that integrating open-source LLMs into enterprise applications comes with complex challenges, including navigating licensing, data usage permissions, output control, and auditing requirements.Enterprises must address strict compliance and security standards, especially in regulated industries, when implementing open-source LLMs. This includes ensuring data privacy, adhering to industry-specific regulations, and maintaining the integrity of sensitive information.Tailoring open-source LLMs to specific enterprise needs requires significant customization. Enterprises need to modify these models to align with their unique operational, compliance, and ethical standards.Potential solutions to the issues inherent with the use of LLMs involve employing strategies for effective management of open-source LLMs, include:Selective Model Adoption: Carefully selecting open-source models that best fit the enterprise's technical and compliance requirements.Data...

"There is no one way to do recruitment right, there are many ways to do it right but even more ways to do it badly." -Bas van de Haterd

"The reality is that we're in an era of experimentation. We have to experiment continuously." -Kevin Wheeler Summary:

In this episode of Science 4-Hire I welcome two old friends, distinguished Science 4-Hire alumni, and talent acquisition experts, Kevin Wheeler and Bas van de Hatred.

The show is dedicated to a deep dive into their new book "Talent Acquisition Excellence,", which is a practical handbook for those who wish to learn how to apply best practices using the holistic framework created by these two experts as their guide.In our discussion we explore what excellence in talent acquisition actually looks like. In doing so, we delve into the book's key themes, including the transformative role of artificial intelligence in hiring, the necessity for ethical frameworks in AI deployment, and the importance of adapting talent acquisition strategies to fit organizational culture.

One of the most important themes from our conversation is the necessity for talent acquisition professionals to adapt and evolve, emphasizing the need for experimentation and a strategic approach to integrating AI into talent acquisition processes. Kevin and Bas also share their journey of collaboration during the pandemic, highlighting how their perspectives from different corners of the globe have influenced the book's content. The conversation also addresses the challenges of navigating a landscape where technology outpaces policy, underscoring the need for talent leaders to innovate responsibly.Key Takeaways:
Multifaceted Approaches to Talent Acquisition: The book emphasizes that there's no one-size-fits-all strategy for recruitment; success lies in customizing approaches to fit organizational culture.The Critical Role of AI in Hiring: Insights into how AI is reshaping the efficiency and scope of assessments, with a look towards future technologies like interactive holograms.Ethical Use of AI: The discussion sheds light on the ethical implications of AI in hiring, advocating for transparency and human oversight.Adapting to Technological Advances: The authors stress the importance of talent leaders being open to experimentation and adaptation in the face of rapid technological changes.Policy Development on AI Usage: A crucial takeaway is the immediate need for organizations to develop policies regarding candidates' use of AI in applications.Listeners will gain not only a nuanced understanding of the current state and future directions of talent acquisition but also practical advice on navigating these changes. This episode is a must-listen for anyone looking to stay at the forefront of hiring practices in the AI era while staying true to the foundations and frameworks required to do talent acquisition the right way.