Xena Ugrinsky's guest appearances

Xena Ugrinsky

IBM thinkLeaders

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Karen Bhatia

Sameer Maskey

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Stephen Miller

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Today’s guest is Xena Ugrinsky, the CTO and co-founder at Pilot Wave Holdings - a financial sponsor that helps businesses remain competitive in the technological age. Today Xena speaks to us about her experience of seeing the rise in Big Data a decade ago and how it is comparable now to the era of AI, especially learning from how service providers and clients both need to evolve. In addition, Xena will be discussing the transferable lessons from Big Data and applying them to the values of AI. So, if you are interested in implementing AI in your enterprise, then tune in and find out the key lessons to take from Big Data! Xena is also a valued Emerj Plus member, and so if you would like to get more information on AI frameworks, ROI strategies, and AI adoption, you can visit Emerj Plus at emerj.com/p1.

Today’s guest is Xena Ugrinsky, the CTO and co-founder at Pilot Wave Holdings - a financial sponsor that helps businesses remain competitive in the technological age. Today Xena speaks to us about her experience of seeing the rise in Big Data a decade ago and how it is comparable now to the era of AI, especially learning from how service providers and clients both need to evolve. In addition, Xena will be discussing the transferable lessons from Big Data and applying them to the values of AI. So, if you are interested in implementing AI in your enterprise, then tune in and find out the key lessons to take from Big Data! Xena is also a valued Emerj Plus member, and so if you would like to get more information on AI frameworks, ROI strategies, and AI adoption, you can visit Emerj Plus at <a href="http://emerj.com/p1" rel="nofollow" target="_blank">emerj.com/p1</a>.

Adapting a Services Firm to AI, Lessons from the Era of Big Data - with Xena Ugrinsky of Pilot Wave

Who is most responsible for the ethical growth of AI--technology vendors, companies, or governmental entities? How can we ensure that technology is augmenting intelligence? How do we get around the tension between profitability and social responsibility? In this episode of IBM thinkLeaders podcast, we are joined by Xena Ugrinsky (Founder of GenreX) and Meeri Haataja (CEO and Co-Founder of Saidot. We talk to Xena and Meeri about business transformation, senior management’s role in job reskilling, and the importance of having a multidisciplinary team capable of an iterative process. We also get into the problem of thinking of AI as magic, Finland’s national AI program, the need for collaboration within the industry, and how it’s difficult to determine the best application for AI.“[I]t takes a village [for AI and ethics]. Enterprise-wide solutions take an even larger village and so when you have a mismatch of values, you immediately have a deterioration of the value the collective can bring. Ethics and AI are probably one of the, one of the most challenging topics that we are going to have to wrestle with over the next couple of years.” -Xena Ugrinsky, Founder of GenreX“[A]sking what's the best application for AI is like it will be asking what's the best use case for [the] Internet. So it's sort of like, it's impossible. It goes across everything.”-Meeri Haataja, CEO and Co-Founder of SaidotConnect with us + the guests:@IBMthinkLeaders@QueenOfDataTech@meerihaatajaBIOSXena Ugrinsky is the founder &amp; principal of Genre-X, and the author of Enterprise AI: Your Field Guide to the New Business Normal. She frequently speaks on topics related to the application of advanced analytics to systems modernization and business transformation. She provides strategy and client advisory related to implementing advanced analytics maturity in support of solving business issues for finance, operations, sales, and marketing.Prior to founding GenreX, Ms. Ugrinsky was a Senior Vice President of Analytics, Cloud, and Strategy in the Civil Commercial Group at Booz Allen Hamilton. In that role, she was part of the leadership team that led Booz Allen’s efforts defining a commercial strategy that translated offerings and services provided in the federal and civil markets to the commercial market.Meeri is the CEO and Co-Founder of Saidot, a start-up with a mission for enabling responsible AI ecosystems. Saidot develops technology and services for AI risk management, focusing on transparency, accountability and agreements on AI. Meeri was the chair of ethics working group in Finland’s national AI program that submitted its final report in March 2019. In this role she initiated a national AI ethics challenge and engaged more than 70 organizations to commit to ethical use of AI and define ethics principles. Meeri is also the Chair of IEEE’s initiative for the creation of AI ethics certificates in ECPAIS program (Ethics Certification Program for Autonomous and Intelligent Systems). Meeri is an Affiliate of the Berkman Klein Center for Internet &amp; Society at Harvard University during the academic year 2019-2020 with a focus on projects related to building citizen trust through AI transparency as well as developing certifications for judicial AI systems. Meeri is an active advocate of responsible and human-centric AI. She’s an experienced public speaker regularly speaking at international conferences and seminars on AI opportunities and AI ethics.

Who is most responsible for the ethical growth of AI--technology vendors, companies, or governmental entities? How can we ensure that technology is augmenting intelligence? How do we get around the tension between profitability and social responsibility? In this episode of IBM thinkLeaders podcast, we are joined by Xena Ugrinsky (Founder of GenreX) and Meeri Haataja (CEO and Co-Founder of Saidot. We talk to Xena and Meeri about business transformation, senior management’s role in job reskilling, and the importance of having a multidisciplinary team capable of an iterative process. We also get into the problem of thinking of AI as magic, Finland’s national AI program, the need for collaboration within the industry, and how it’s difficult to determine the best application for AI. “[I]t takes a village [for AI and ethics]. Enterprise-wide solutions take an even larger village and so when you have a mismatch of values, you immediately have a deterioration of the value the collective can bring. Ethics and AI are probably one of the, one of the most challenging topics that we are going to have to wrestle with over the next couple of years.” -Xena Ugrinsky, Founder of GenreX “[A]sking what's the best application for AI is like it will be asking what's the best use case for [the] Internet. So it's sort of like, it's impossible. It goes across everything.”-Meeri Haataja, CEO and Co-Founder of Saidot Connect with us + the guests: @IBMthinkLeaders @QueenOfDataTech @meerihaataja BIOS Xena Ugrinsky is the founder &amp; principal of Genre-X, and the author of Enterprise AI: Your Field Guide to the New Business Normal. She frequently speaks on topics related to the application of advanced analytics to systems modernization and business transformation. She provides strategy and client advisory related to implementing advanced analytics maturity in support of solving business issues for finance, operations, sales, and marketing. Prior to founding GenreX, Ms. Ugrinsky was a Senior Vice President of Analytics, Cloud, and Strategy in the Civil Commercial Group at Booz Allen Hamilton. In that role, she was part of the leadership team that led Booz Allen’s efforts defining a commercial strategy that translated offerings and services provided in the federal and civil markets to the commercial market. Meeri is the CEO and Co-Founder of Saidot, a start-up with a mission for enabling responsible AI ecosystems. Saidot develops technology and services for AI risk management, focusing on transparency, accountability and agreements on AI. Meeri was the chair of ethics working group in Finland’s national AI program that submitted its final report in March 2019. In this role she initiated a national AI ethics challenge and engaged more than 70 organizations to commit to ethical use of AI and define ethics principles. Meeri is also the Chair of IEEE’s initiative for the creation of AI ethics certificates in ECPAIS program (Ethics Certification Program for Autonomous and Intelligent Systems). Meeri is an Affiliate of the Berkman Klein Center for Internet &amp; Society at Harvard University during the academic year 2019-2020 with a focus on projects related to building citizen trust through AI transparency as well as developing certifications for judicial AI systems. Meeri is an active advocate of responsible and human-centric AI. She’s an experienced public speaker regularly speaking at international conferences and seminars on AI opportunities and AI ethics.

AI Ethics & Business Transformation w/ Xena Ugrinsky and Meeri Haataja

[Audio] Podcast: Play in new window | DownloadSubscribe: Google Podcasts | Spotify | Stitcher | TuneIn | RSSXena Ugrinsky has spent over the last 20 years of her career in technology enabled transformation. The last eight years of those have been focused on the application of data science for corporate performance management. She has a new book titled “Enterprise AI-Your Field Guide to the New Business Normal”.Episode Links:  Xena Ugrinsky’s LinkedIn: https://www.linkedin.com/in/xenaugrinsky/ Xena Ugrinsky’s Twitter:  https://twitter.com/QueenOfDataTech?s=20 Xena Ugrinsky’s Website: https://genrexconsulting.com/https://www.pilotwaveholdings.com/ Podcast Details: Podcast website: https://www.humainpodcast.comApple Podcasts:  https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009Spotify:  https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpSRSS: https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9YouTube Full Episodes: https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1ragYouTube Clips:  https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videosSupport and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: https://www.patreon.com/humain/creators– Twitter:  https://twitter.com/dyakobovitch– Instagram: https://www.instagram.com/humainpodcast/– LinkedIn: https://www.linkedin.com/in/davidyakobovitch/– Facebook: https://www.facebook.com/HumainPodcast/– HumAIn Website Articles: https://www.humainpodcast.com/blog/Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:39) –At first technology was process optimization. Then there were better individual tools for doing analysis. So there you have spreadsheets. Analytics began to enable in the second phase the ability to do things like driver based forecasting trending analysis. And the third phase and the one that we find ourselves in today is the beginning of applying truly modern mathematical methods in the form of data science to technology(06:41) – Technology isn't the hurdle anymore, it's people, it's process, it's culture, it's organizational structure. (08:23) – Spreadsheets are too deeply ingrained in how business works (10:58) – Siloing of functions was causing a bottleneck of data that prevented executive teams from having the right information at the right time at their fingertips to make a decision(13:15) – Analytics application proliferation have become more accessible to the business community, then the IT organization completely loses control of their tech portfolio and managing costs(16:56) – The things that have to change in an organization to become an intelligent enterprise don't involve technology at all. You have to consider the people and a culture of inclusiveness that moves away from information as power to empowering everyone with the information(20:09) – Our traditional organizational structures need to be rethought. And it starts at the top with re configuring the responsibilities of the C-suite(23:15) – AI as a whole is not going to be the new spreadsheet, AI as a whole describes the transformation of applied data science(24:23) – Organizations fall into three categories: organizations built up and architected as a data company, traditional organizations that have been early adopters to solve something or to embed it in their product, and the ones that don’t know what is the right way to get started in data science(32:43) – Organic transformation: when you change people, you change the entire organization(34:00) – The winners in this race will be transforming so that their organizations are truly data-driven. If you miss this boat, you won't exist as a companyAdvertising Inquiries: https://redcircle.com/brandsPrivacy &amp; Opt-Out: https://redcircle.com/privacy

[Audio] Podcast:<a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank"> </a><a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank">Play in new window</a> |<a href="https://www.listennotes.com/podcasts/humain-podcast-artificial-intelligence-data-fBRret2PTiU/" rel="nofollow" target="_blank"> </a><a href="https://www.listennotes.com/podcasts/humain-podcast-artificial-intelligence-data-fBRret2PTiU/" rel="nofollow" target="_blank">Download</a>Subscribe:<a href="https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5yZWRjaXJjbGUuY29tLzk5MTEzZjI0LTJiZDEtNDMzMi04Y2QwLTMyZTA1NTZjOGJjOQ" rel="nofollow" target="_blank"> </a><a href="https://podcasts.google.com/feed/aHR0cHM6Ly9mZWVkcy5yZWRjaXJjbGUuY29tLzk5MTEzZjI0LTJiZDEtNDMzMi04Y2QwLTMyZTA1NTZjOGJjOQ" rel="nofollow" target="_blank">Google Podcasts</a> |<a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank"> </a><a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank">Spotify</a> |<a href="https://www.stitcher.com/show/humain" rel="nofollow" target="_blank"> </a><a href="https://www.stitcher.com/show/humain" rel="nofollow" target="_blank">Stitcher</a> | <a href="https://tunein.com/podcasts/Technology-Podcasts/HumAIn-p1224678/" rel="nofollow" target="_blank">TuneIn</a> | <a href="https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9" rel="nofollow" target="_blank">RSS</a>Xena Ugrinsky has spent over the last 20 years of her career in technology enabled transformation. The last eight years of those have been focused on the application of data science for corporate performance management. She has a new book titled “Enterprise AI-Your Field Guide to the New Business Normal”.Episode Links:  Xena Ugrinsky’s LinkedIn: <a href="https://www.linkedin.com/in/xenaugrinsky/" rel="nofollow" target="_blank">https://www.linkedin.com/in/xenaugrinsky/</a> Xena Ugrinsky’s Twitter:  <a href="https://twitter.com/QueenOfDataTech?s=20" rel="nofollow" target="_blank">https://twitter.com/QueenOfDataTech?s=20</a> Xena Ugrinsky’s Website:<a href="https://welcome.ai/" rel="nofollow" target="_blank"> </a><a href="https://genrexconsulting.com/" rel="nofollow" target="_blank">https://genrexconsulting.com/</a><a href="https://www.pilotwaveholdings.com/" rel="nofollow" target="_blank">https://www.pilotwaveholdings.com/</a> Podcast Details: Podcast website: <a href="https://www.humainpodcast.com/" rel="nofollow" target="_blank">https://www.humainpodcast.com</a>Apple Podcasts: <a href="https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009" rel="nofollow" target="_blank"> </a><a href="https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009" rel="nofollow" target="_blank">https://podcasts.apple.com/us/podcast/humain-podcast-artificial-intelligence-data-science/id1452117009</a>Spotify: <a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank"> </a><a href="https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS" rel="nofollow" target="_blank">https://open.spotify.com/show/6tXysq5TzHXvttWtJhmRpS</a>RSS: <a href="https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9" rel="nofollow" target="_blank">https://feeds.redcircle.com/99113f24-2bd1-4332-8cd0-32e0556c8bc9</a>YouTube Full Episodes: <a href="https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag" rel="nofollow" target="_blank">https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag</a>YouTube Clips: <a href="https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos" rel="nofollow" target="_blank"> </a><a href="https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos" rel="nofollow" target="_blank">https://www.youtube.com/channel/UCxvclFvpPvFM9_RxcNg1rag/videos</a>Support and Social Media:  – Check out the sponsors above, it’s the best way to support this podcast– Support on Patreon: <a href="https://www.patreon.com/humain/creators" rel="nofollow" target="_blank">https://www.patreon.com/humain/creators</a>– Twitter: <a href="https://twitter.com/dyakobovitch" rel="nofollow" target="_blank"> </a><a href="https://twitter.com/dyakobovitch" rel="nofollow" target="_blank">https://twitter.com/dyakobovitch</a>– Instagram:<a href="https://www.instagram.com/humainpodcast/" rel="nofollow" target="_blank"> </a><a href="https://www.instagram.com/humainpodcast/" rel="nofollow" target="_blank">https://www.instagram.com/humainpodcast/</a>– LinkedIn: <a href="https://www.linkedin.com/in/davidyakobovitch/" rel="nofollow" target="_blank">https://www.linkedin.com/in/davidyakobovitch/</a>– Facebook: <a href="https://www.facebook.com/HumainPodcast/" rel="nofollow" target="_blank">https://www.facebook.com/HumainPodcast/</a>– HumAIn Website Articles:<a href="https://www.humainpodcast.com/blog/" rel="nofollow" target="_blank"> </a><a href="https://www.humainpodcast.com/blog/" rel="nofollow" target="_blank">https://www.humainpodcast.com/blog/</a>Outline: Here’s the timestamps for the episode: (00:00) – Introduction(02:39) –At first technology was process optimization. Then there were better individual tools for doing analysis. So there you have spreadsheets. Analytics began to enable in the second phase the ability to do things like driver based forecasting trending analysis. And the third phase and the one that we find ourselves in today is the beginning of applying truly modern mathematical methods in the form of data science to technology(06:41) – Technology isn't the hurdle anymore, it's people, it's process, it's culture, it's organizational structure. (08:23) – Spreadsheets are too deeply ingrained in how business works (10:58) – Siloing of functions was causing a bottleneck of data that prevented executive teams from having the right information at the right time at their fingertips to make a decision(13:15) – Analytics application proliferation have become more accessible to the business community, then the IT organization completely loses control of their tech portfolio and managing costs(16:56) – The things that have to change in an organization to become an intelligent enterprise don't involve technology at all. You have to consider the people and a culture of inclusiveness that moves away from information as power to empowering everyone with the information(20:09) – Our traditional organizational structures need to be rethought. And it starts at the top with re configuring the responsibilities of the C-suite(23:15) – AI as a whole is not going to be the new spreadsheet, AI as a whole describes the transformation of applied data science(24:23) – Organizations fall into three categories: organizations built up and architected as a data company, traditional organizations that have been early adopters to solve something or to embed it in their product, and the ones that don’t know what is the right way to get started in data science(32:43) – Organic transformation: when you change people, you change the entire organization(34:00) – The winners in this race will be transforming so that their organizations are truly data-driven. If you miss this boat, you won't exist as a company Advertising Inquiries: <a href="https://redcircle.com/brands" rel="nofollow" target="_blank">https://redcircle.com/brands</a> Privacy &amp; Opt-Out: <a href="https://redcircle.com/privacy" rel="nofollow" target="_blank">https://redcircle.com/privacy</a>

How Traditional Companies Can Transform to Remain Competitive in the Age of AI with Xena Ugrinsky