Enterprise AI governance insights from ScaleUp:AI

1. Responsible AI is the path forward

The model-centric view of AI is passing. More organizations realize the potential of Ethical AI. They also see the damage of unregulated AI. There's inherently significant bias baked into AI models. Within any industry, this bias harms your business, your people, and who you serve. It reflects outwards to society if not kept in check.

Implementing fairness and bias detection within your machine learning technology must happen before scaling. Without it, bias only scales as production does. It ultimately affects data, decision-making, and outcomes. All of which affect profitability.

Every enterprise is deploying AI. Almost none can see the work they're deploying it into.

2. Building Ethical AI starts with being proactive

When asked why Reejig sought an independent audit, Siobhan Savage turned to the responsibility of organizations. Leaders need to understand their own AI. They must invest in keeping it fair and unbiased continuously.

AI often affects not just your own organization. It affects customers and partners. Proactively understanding how your AI works is essential. Learn how bias is created. And in turn, how to eliminate it. Investing resources to keep it ethical represents your commitment. It shows transparency as a business to create positive impact.

The answer: you can't be the only source auditing AI. The way to keep AI honest, fair, and ethical is independent auditing. Reejig became the world's first to do this.

"A lot of prehistoric bias is baked into AI models. So we wanted to make sure we were causing no harm in any decisions. We're working for really large global enterprises. They make decisions on people's most important decisions: their careers. [Having our Ethical AI independently audited] meant we weren't pre-baking in any bias. We could tell our customers, 'here's an independent audit telling you what we've done and the impacts.'"

— Siobhan Savage, CEO and Co-Founder, Reejig

3. AI changes how organizations think about people and potential

Workforce strategy has only been invited to the AI conversation recently. Largely due to the seismic shifts COVID caused. Now, having the technology to change how people source, hire, move, and retain talent creates real impact. Seeing talent based on skills and potential alone gives organizations power. They switch their hiring mindset. They decrease costs. They maximize their rate of placing the right people in the right roles.

4. Communicate your responsibility toward Ethical AI

As AI's impact on society grows, organizations must speak out. Their commitment, proactiveness, and intent for good matter more than ever.

Leaders need to discuss openly how their AI applies to new data sets. They must explain how it remains ethical at scale. Human-centered AI focused on doing good for people, business, and society will attract contributors and stakeholders.

"We believe in a world where no matter who you are, your background, your skin color, your gender, whether you're a veteran, everyone should have access to a meaningful career. Instead of people being considered based on job titles or appearance, it's about focusing on skills, potential, and passions. That's the world we're obsessed with. We believe we should all get there."

— Siobhan Savage, CEO and Co-Founder, Reejig