Kenneth Fricklas (Principal)
Ken Fricklas is an experienced CTO, VP of engineering, speaker, author, and lean strategy consultant. He was a senior manager at Google Search, is a member of the leadership team at 10.10.10, co-founder of Mallfinder Network (now Placewise), Disinformation, CovidCheckColorado and many other startups, former innovation lead at CableLabs, and a TechStars mentor. Currently he also serves as the innovation chair of the Colorado CleanTech Consortium.
His primary interests are in improving the world through technical means - lessening the effects of wicked problems, and handling complexity through risk management, creative entrepreneurship and strategic leadership. He is certified in leadership with complex systems from Cornell and Applied Information Economics from Hubbard Decision Research, and has written several books on programming and AI.
Robert Monaco (Principal)
Robert Monaco is a visionary leader and advocate for ethical AI, founding the Boulder Coalition for Human Centric AI, committed to building community consensus and developing transparent AI systems. With over 25 years in the tech industry, Robert has a proven track record in building cross-organizational relationships to deliver enterprise software solutions to companies of all sizes.
Robert is an IBM Alum with a decade of experience addressing business demands with technology with a focus on data management, data privacy, RPA, and AI solutions. Robert's recent certifications include AWS Cloud Foundations and Applying Business Ethics from Cornell Law School.
Turaco Strategy embodies the vision and vibrancy of its namesake, the Turaco bird, to deliver standout ethical AI consulting services that elevate your technology with a spectrum of global perspectives. We strategize with agility and insight, ensuring your AI solutions soar with integrity and innovation.
Our TURA framework stands for "Transparent, Universal, Responsible, Accountable," encapsulating the four cornerstone principles essential to ethical AI development:
Transparent: Advocating for openness in algorithms, data usage, and decision-making processes to ensure that AI operations can be understood and scrutinized by stakeholders.
Universal: Ensuring inclusivity and fairness, so AI systems do not perpetuate bias and are designed to benefit a broad range of populations without discrimination.
Responsible: Emphasizing the importance of creating AI that acts in the best interest of humans, with consideration for long-term impacts and ethical implications of AI technology.
Accountable: Establishing clear guidelines for accountability, so there is a mechanism for redress if AI systems cause harm or operate outside of ethical boundaries.
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