Whatever the general public may think of AI, businesses are on board, seeing the great potential of AI for optimizing existing systems and creating new ones. AI is no longer viewed as simply an option for most industries, but as an inevitability.

As businesses with the agility and budgets lead the charge on the development and implementation of AI, and others begin to follow, it can be easy to move at the speed of innovation without viewing AI through a human lens. In this spirit, panelists convened at the 2024 Catalyst Honours in Toronto on 7 October 2024 to discuss “Shaping an Inclusive Future Through Generative AI.”

Kathleen Taylor, Chair, Element Fleet Management, Altas Partners, and The Hospital for Sick Children, spoke about the portfolio of organizations she works with, saying they are generally optimistic about an AI-enhanced future of work. “There’s such enormous opportunity associated with all of this,” she said.

This sentiment was echoed by discussion moderator David Morgenstern, President, Accenture Canada, who said, “We published a paper at Microsoft this spring that said even traditional Canadian adoption [of AI] would add the equivalent of an insurance or retail sector to Canada.” That translates to an annual economic windfall of $180 billion in labor productivity gains by 2030.

AI can assist in innovation for good

Panelists then shifted their focus to implementation. Jennifer Freeman, CEO of PeaceGeeks,  highlighted AI’s impact on bridging the gaps between users and government. “We’re really utilizing AI in our digital tools as an equalizer,” she said.

For immigrants, there are many barriers (like language and technology) to accessing resources. PeaceGeeks partnered with Accenture to create an AI virtual career coaching platform that can help people practice interviewing, soft skills, and job matching for permanent residency.

As of 7 October 2024, the platform, which rolled out in June, has already had over 100,000 unique users.

AI can perpetuate current biases

Panelists agreed that a healthy dose of caution is needed when creating platforms that rely on AI. Pamela Pelletier, Country Leader & Managing Director, Canada, Dell Technologies, said, “It’s all about the data. Garbage in, garbage out. If you have data that is skewed or that is biased, then you’re going to have a problem.”

She gave the example of AI chatbots, which can “hallucinate”. “Where does ChatGPT get their information from? Twitter, whatever, all these places. So, the data itself is potentially biased.”

Aneela Zaib, Founder & CEO, emergiTEL, said, “The fact is that the LLM (large language model) models that we have on our hands currently, we don’t know how they’re trained or which data they are trained on.”

AI must be fed the right data

What can be done to combat this issue? How can we prevent the same blind spots in the future?

Zaib is already working on solutions. “One of the ways we have tried to overcome [this] is we have fine-tuned these models based on the dataset that are inclusive in nature already. So, when you give a dataset to this tool which is already inclusive and you define set prompts (and there’s a lot of detail…that we can go crazy over), the bottom line is that you have to be very careful in using these systems, giving them the guardrails, and at the same time auditing these systems at the end with the results that you are getting.”

Her company’s tools deliver diverse job candidates to client companies, and AI is part of those tools. When they audit the results that AI delivers, if they find a job or a skillset that isn’t being filled by candidates in certain communities, they analyze those results, fine-tune them, and run the AI model again. Ongoing stewardship of these AI tools and models is part of the process, especially when the work is so important. Zaib said, “Diversity is a practice that we have to do every day.”

DEI and AI can work together

Pelletier echoed this sentiment, saying, “We have the opportunity with the tech that exists now to actually bring people in who have been historically forgotten or left behind.”

Organizations that use AI must do their part. Pelletier said, “As an organization, we have the responsibility when we’re training models to have that data reflect the values we have as an organization. So, it is really important that we take that data and we curate the data to reflect those values… and then we’ll have a very positive outcome.”

She added that DEI and AI can and should work together to further humanity’s best interests. “We need to have our DE&I representation, those folks, at the table at the beginning as we implement the AI projects. And they need to have the ability or authority to hit that pause button or that stop button. If one were analyzing the data, if something is inappropriate, they can pause that and go and correct it,” she said.

Be intentional with AI

As organizations rush to add AI to various aspects of their businesses, it’s important to take the time to do it correctly. If a company doesn’t have high customer service traffic, it probably doesn’t need an AI chatbot. If a company has a large marketing department, it probably doesn’t need to train AI to write articles. And if a company cares deeply about its values, it shouldn’t license an LLM trained on biased datasets.

Taylor summed it up perfectly: “We can make this work, as long as we’re building capably, testing well, utilizing but then coming back around and making sure that what comes out the other end is exactly the outcome we would have hoped for, whether that’s a new recruit, a system that’s delivering a new customer offering, whatever it may be.”

Want to know about next year’s Catalyst Honours? Sign up now and we’ll email you when registration opens.

The post Global CEOs share insights on AI implementation appeared first on Catalyst.

As we enter the Age of AI, we are transitioning from a knowledge economy to a relationship economy. This shift underscores the increasing value of interpersonal skills that AI cannot replicate critical thinking, empathy, creativity, adaptability, trust, and collaboration. In this landscape, women continue to face unique challenges and opportunities in the workplace. This webinar will highlight the importance of these essential skills and provide strategies to empower women to thrive in the relationship economy.

Investing in and valuing interpersonal skills is crucial for the success of individuals, businesses, and effective human-AI collaboration. Businesses that prioritize these skills foster inclusive environments that leverage diverse talents and perspectives. Empowering women in the relationship economy helps create a future where technology and human connection coexist harmoniously, benefiting organizations, their employees, and their communities.

Join our panel of experts to discuss:

• How AI is transforming the relationship economy and affecting women at work
• Best practices for implementing initiatives and structures that value soft skills
• Findings from Catalyst’s Adapt or Fail research on how to build adaptability as a skill

Note: Please log in to the website with your Catalyst Supporter organization email to access registration. If you are NOT a Catalyst Supporter, please email us to proceed with payment and registration. For questions, please contact catalystevents@catalyst.org.

Catalyst is recognized by SHRM to offer Professional Development Credits (PDCs) for SHRM-CP® or SHRM-SCP® recertification activities.

The post AI, Equity, and the Future of Work: Empowering Women in the Relationship Economy appeared first on Catalyst.

The Catalyst webinar “How to Use Generative AI Free of Gender and Racial Bias” explored strategies for creating ethical AI practices that promote equity and inclusion in the workplace. By understanding and mitigating its biases, organizations can leverage AI as a tool for progress rather than one that reinforces inequalities.

Moderated by Julie Cafley, Executive Director, Catalyst Canada, the panel included Cathy Cobey, Global Responsible AI Co-Lead, EY; Noelle Russell, Chief AI Officer, AI Leadership Institute; and Michael Thomson, Executive Vice President, Edelman.

Here are our top five insights from the discussion:

1. AI education is essential to avoid pitfalls.
   AI can enhance human capabilities, yet it also carries inherent risks. Russell likened AI to magic, highlighting its capacity to leverage past data and behaviors to refine decision making, while Cobey noted that “AI is still human controlled. Maintaining this oversight is essential in AI development. There’s always a magician behind every magic trick.”

   All panelists agreed that users need better education to utilize AI effectively and avoid potential risks. “There is a dark side to this magic,” Thomson warned. “AI’s transformative power offers great opportunities but requires robust risk management strategies to protect against its pitfalls.”

2. Understand that all AI is inherently biased.
   AI systems can unintentionally absorb biases from their training data. “No dataset or person is free of bias,” Thomson said.

   Data scientists aim to create holistic, empathetic, and inclusive models, believing that their innovations will deliver beneficial outcomes. “At the onset, these models are like baby tigers—cute and full of potential,” Russell said. “However, critical questions about their long-term impact are often overlooked, leading to significant challenges as AI models mature and become operational. Ensuring diverse representation throughout the development process is essential to minimize biases effectively.”

3. Implement strong AI principles.
   AI standards should be ingrained into an organization’s core values, not treated as an afterthought. “AI principles need to be like water in a wave, woven through everything we do,” said Russell. She also advised that leadership must shift their thinking and incorporate these principles into the organization’s core values.

   Cobey added that EY updated their AI principles in September 2023 to include sustainability, noting the high level of computer processing, energy, and water usage involved in running large language models (LLMs) and other types of AI models. She also pointed out that some of the principles can be in conflict with each other and require trade-offs. “Sometimes security works against transparency and accuracy against explainability,” she said. “You have to choose which principles and values are the most important, depending on the AI use case.”

4. Embrace AI—cautiously—for a competitive advantage.
   “The best advice I can give is to just start using AI,” Thomson said. “It may be intimidating at first, so start with small, manageable tasks. AI is a tool with limitations. It’s like an imperfect first draft. Don’t blindly share AI-generated information.” He likened it to using a calculator for complex math, saying “Without it, I’d struggle, but with it, I’m efficient. AI can be that tool for you. Organizations using AI effectively will outpace those that aren’t, making AI training essential for everyone. We need to take advantage of these tools, particularly when other people aren’t.”

5. AI needs all our perspectives for a better future.
   Active participation in AI development is the way forward. “We need to help it make better decisions. We are part of the solution,” Cobey said, adding that users don’t need to be tech savvy.

   Russell stressed the importance of diverse perspectives in building AI systems that serve everyone, saying, “Don’t build for people without those people. It’s important to show, not tell, when advocating for diversity and inclusion.” Outsourcing how AI will be implemented at your organization, she cautioned, is ill-advised without diverse representation.

As organizations navigate the complex challenges of integrating generative AI, they should focus on maintaining ethical standards that promote inclusivity and lessen biases. By conscientiously implementing AI practices that prioritize diversity, equity, and inclusion, organizations will reap the enormous benefits of this transformative technology while continuing to advance workplace equity and support their core values.

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The post Leverage AI While Avoiding Its Risks and Biases (Blog Post) appeared first on Catalyst.

But that understanding will require careful consideration of the risks and biases AI tools and processes tend to exhibit—from gender and racial biases to flat-out inaccuracies in output. With that foundation of awareness, business leaders set themselves up for success in creating a workplace that is fit for inclusion in the new era of work. 

Watch this webinar to hear our panel of experts discuss: 

• How companies are tackling AI and the future of work, from AI councils, committees, and chief officers.
• The landscape of AI and business strategy, including legislative regulations, common biases, and risks.
• The invigorating prospects for success in leveraging AI to support a holistic approach to diversity, equity, and inclusion.

Speakers

Cathy Cobey, Global Responsible AI Co-Lead, EY

Noelle Russell, Chief AI Officer, AI Leadership Institute

Michael Thomson, Executive Vice President, Edelman

Moderator

Julie Cafley, Executive Director, Catalyst Canada

Recording Available only to Catalyst Supporters. Please log in to watch the recording.

The post Webinar Recording: How to Use Generative AI Free of Gender and Racial Bias appeared first on Catalyst.

But that understanding will require careful consideration of the risks and biases AI tools and processes tend to exhibit—from gender and racial biases to flat-out inaccuracies in output. With that foundation of awareness, business leaders set themselves up for success in creating a workplace that is fit for inclusion in the new era of work. 

Join this webinar to hear our panel of experts discuss: 

• How companies are tackling AI and the future of work, from AI councils, committees, and chief officers.
• The landscape of AI and business strategy, including legislative regulations, common biases, and risks.
• The invigorating prospects for success in leveraging AI to support a holistic approach to diversity, equity, and inclusion.

Speakers

Cathy Cobey, Global Responsible AI Co-Lead, EY

Noelle Russell, Chief AI Officer, AI Leadership Institute

Michael Thomson, Executive Vice President, Edelman

Moderator

Julie Cafley, Executive Director, Catalyst Canada

For questions, please contact catalystevents@catalyst.org.

Catalyst is recognized by SHRM to offer Professional Development Credits (PDCs) for SHRM-CP® or SHRM-SCP® recertification activities.

The post How to Use Generative AI Free of Gender and Racial Bias–Trending Topic Webinar appeared first on Catalyst.

The post Use AI to Attract a More Diverse Candidate Pool (Tool) appeared first on Catalyst.

Elias sat on a panel at last month’s Catalyst Honours Conference & Dinner in a discussion moderated by Rubiena Duarte, Vice President of Global Diversity and Inclusion, Procore. The session, “Advancing Representation and Inclusion Through Responsible AI,” brought together perspectives of tech, AI ethics, and diversity, equity, and inclusion (DEI) professionals.

Panelists Karlyn Percil, Chief Equity Officer, KDPM Equity Institute, and Anna Jahn, Director of Public Policy and Learning, Mila (Quebec AI Institute), discussed the human biases embedded in AI and how we can build the technology differently.

“I wanted to address the elephant in the AI room: current AI is built on the white racial frame. We have to talk about the dominant culture and going beyond DEI to look at human equity,” said Percil.

Jahn added: “This is not a technology that fell from the sky… We built it. We have the agency to build it differently.”

To disrupt patterns of systemic prejudice, Percil recommended that organizations focus on inclusive AI strategies and bringing in a wide range of voices within and outside their companies. “If we take the time to redirect our attention, organizations can start building responsible AI by starting where you are… What works within your company? Does your DEI strategy include AI?” she said.

“Claim your spot in the conversation,” Jahn encouraged the audience—coders and programmers should not be the only people deciding how AI algorithms function or which datasets they use.

Elias agreed with Jahn, saying, “We need people with backgrounds in ethics, legal and compliance, philosophy, security, technology, to join us at the table. It takes a village to build AI systems.”

Key takeaways from the session include:

• Substantial barriers exist for women and underrepresented groups when entering and succeeding in technology and AI fields. Companies must be proactive about dismantling obstacles through updated hiring practices, mentorship programs, inclusive team cultures, and more.
• Modern AI systems often reflect and amplify existing human biases, leading to unfair and unethical results. We have the responsibility and power to build these systems differently in fair and inclusive ways from the ground up.
• To create responsible AI, organizations need to take a systemic approach that considers ethics, compliance, security, and philosophy alongside technical expertise. Representatives from all backgrounds and identities should have a seat at the table.
• Rather than solely focusing on performance benchmarks, responsible AI also requires us to prioritize bias mitigation and fairness across gender, race, and other identity factors. Some loss of efficiency may be a necessary tradeoff.
• As the global workplace begins to embrace AI technology, the time is now to redirect your attention to rebuilding its systems in a way that reflects your company’s values and a vision that prioritizes human equity and social good.

As the AI tool used to help write this summary blog wrote, waxing poetic: “The future remains unwritten—it is up to us to write it inclusively.”

Discover more insights from 2023 Catalyst Honours

The post What Is ‘Responsible AI’? Panelists Weigh in (Blog Post) appeared first on Catalyst.

Join us for a discussion on the evolving intersection of AI and equity, delving deep into the transformative potential that AI holds for shaping a future of work grounded in fairness. As a group, we will reflect on the ethical dimensions of AI deployment and its consequences on marginalized communities and explore how responsible AI development can be a catalyst for positive change and drive meaningful progress.

Speakers

Vidushi Korczyk, Senior Manager, Strategy and Consulting, Accenture

Sarah O’Flynn, Management Consultant, Accenture

Inga Seelemann, Principal Director, Technology Strategy & Advisory, Accenture

Moderator

Aliya Ansari, Director, Supporter Success, Western Canada, Catalyst

The event will welcome representatives from various roles, including Chief Information Officers, CHROs and other HR/DEI professionals, Technology professionals, and other leaders working to advance equity and inclusion at their organization.

This roundtable is being hosted by Accenture.

The post In-Person Roundtable: Exploring the Impact of AI on Equity and The Way We Work with Accenture appeared first on Catalyst.

Watch this webinar to learn more about the impact of generative AI and other emerging technologies on the way we work now and into the future.

Speakers

Afua Bruce, Founder & Principal, ANB Advisory Group LLC

E. Glen Weyl, Research Lead, Plural Technology Collaboratory, Microsoft Research Special Projects

Dr. Monique Umphrey, Provost/Executive Vice Chancellor of Academic and Student Affairs at Austin Community College District

Anu Puvvada, Metaverse Center of Excellence & KPMG Studio Leader, KPMG LLP

Nicole Jackson, Head of Digital Transformation, Catalyst

Moderator

Lauren Pasquarella Daley, PhD, VP, Head of Product Partnership and Innovation and Lead, Women and the Future of Work, Catalyst

The post Webinar Recording: Exploring the Impact of ChatGPT, AI, and Emerging Technology on Equity and The Way We Work appeared first on Catalyst.