Ideagen Global - Catalyze Magazine - November 2023

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A S S E S S I N G A N D S O L V I N G F O R T H E D A T A D I V I D E Gretchen: Its benefits, of course, are that we get access to incredible information that makes us smarter and more productive. It makes us safer and more resilient as citizens and companies across the globe. Still, it also starts to create an inequity with countries that don't have access to data, are in geopolitical climates where they won't give access to data, or poor or underserved communities where they can't afford to leverage that kind of data. What's happening is the commercial side of the business has the money and the means to leverage data in a very smart way, but when we think about the public sector, NGOs, and nonprofits, or we think about citizens in different communities or different countries across the globe, there's none. We're actually creating a larger set of inequities between people. They don't have the same access or the same ability to use those insights, and it becomes a marginalization between them. CATALYZE MAGAZINE | 7
A S S E S S I N G A N D S O L V I N G F O R T H E D A T A D I V I D E Gretchen: For the data divide, first, we have to wake up and realize that data is driving the way we think and make decisions. We're seeing this every day with AI. We also know that we're pulling people further apart because it's the haves and the have-nots. I'll give you a real-world example: When we were in the pandemic, think about the data that was used to help. Quite frankly, people understood where the infection rate was and how safe you were in your community. Think about the notifications received on exposures. When COVID landed in Seattle, The University of Washington Medical was one of the first data science groups to take advantage of data and then share that out into the world. MayoClinic and others caught on, but if you were lucky enough to have those resources, you essentially had some protection as a citizen. That's the good side, but there's a bad side. When UCSF was partnering on that same kind of data, public health officials were trying to get information out into San Francisco. However, the data sets were so big and too complex, and the company that was assessing the data was using fax machines. This is a true story. So even though you had this massive amount of data, the public entities didn't have the infrastructure, the ability, the means, or the digital literacy to capture that. So what did they do? They bought more fax machines if you can believe that. I don't even know if I could use a fax machine anymore, but they used more and more fax machines. So the idea behind that is now you have somebody without those resources. That is the kind of example to bring it into sort of human terms of what this access actually means. George Sifakis & Gretchen O’Hara outside The Nasdaq Marketside George Sifakis interviews Gretchen O’Hara CATALYZE MAGAZINE | 8
Page 1 and 2: B Y I D E A G E N CATALYZE. Novembe
Page 13 and 14: TABLE OF CONTENTS 01 Peter Cuneo Fo
Page 15 and 16: D E V E L O P I N G S U P E R H E R
Page 17 and 18: The Future of AI Within AARP Lana W
Page 19: A S S E S S I N G A N D S O L V I N
Page 23 and 24: F I N D I N G P O W E R I N D I S C
Page 25 and 26: THE MISSION OF HOSA-FUTURE HEALTH P
Page 27 and 28: THE MISSION OF HOSA Marcus: We had
Page 29 and 30: T H E W O R L D H U M A N F O R U M
Page 31 and 32: DEVELOPING CROSS-SECTOR PARTNERSHIP
Page 33 and 34: 2023 Ideagen Global LOCAL CHANGE FO
Page 35 and 36: ENDING THE STIGMA ON MENTAL HEALTH

Ideagen Global - Catalyze Magazine - November 2023

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