Mission

Bias In AI was built in 2019 to bridge awareness and visibility of AI Bias within the expanding commercial marketplace of machine intelligence. Every enterprise and industry will be impacted by core technology stacks, tools, and data, powering both professional and personal interfaces of the future. Gartner predicts 85 percent of AI projects will deliver erroneous outcomes due to bias in data, algorithms, or the teams responsible for managing them.

As this industry will leapfrog to $266 billion by 2027, our primary goal is to empower businesses and consumers everywhere to make better informed, smarter decisions when piloting or launching responsible AI programs through a combination of buy, build and outsource efforts.

Through industry research insights and workshop education, we want to empower venture capitalists, enterprises and government stakeholders with best practices. strategy planning and informed decision making in evolving and quick accelerating AI regulatory environments.

Leadership

Caryn Lusinchi is FHCA (For Humanity Certified Auditor) under EU GDPR and NYC Bias Law and has a certificate in Foundations of Independent Audit of AI Systems (FIAAIS). Most recently, she led product marketing strategy & scalability for Arthur AI which improved ML models for data accuracy, explainability and bias detection. Additionally, she brings 15+ years of combined global enterprise expertise in B-to-C and B-to-B technology (ex-Google, ex-Meta) and strategy roles for product GTM across NA, EMEA, and LATAM. Connect with me on LinkedIn.

Caryn acknowledges that a software platform is only the start for any organization seeking to scale AI. She understands the inherent challenges in putting responsible AI into tactical application inside enterprises, having moderated The Role of Leadership in the Advancement of AI panel for Swiss Cognitive, the World’s Leading AI Network Summit, taught Oregon State Bar’s continuing education course on Challenges in Building Trust in AI/ML, authored articles on explainable AI and NYC bias law and was a contributor and co-author to All Tech is Human’s publication: The Business Case for AI Ethics: Moving From Theory to Action.