Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

By Felipe FloresTechnology
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Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science episodes

  • #131 AI & Technology, Key Drivers for Scaling and Optimising the Value Chain with Steve Monaghan – EVP, Chief Digital Officer

    Steve Monaghan is the Chief Digital Officer at Riyad Bank. He has a series of investments in banking and insurance using AI and new technologies in order to improve efficiency.

    He started out as a commercial pilot working 22 hours a day, running the aviation company during the day and flying at night. His first contact with data came when he started using spreadsheets to automate tasks and accelerate the time in which he got them done. His career then moved from flying into technology.

    For Steve, the three core laws of technology that drive data science and AI are:

    • Moore's Law: processing power doubles every 18 months for the same cost.
    • Metcalfe's Law: the value of a network grows by the square of the network's size.
    • Kryder's Law: storage doubles every 13 months for the same cost.

      • He believes these 3 laws encompass the ability you have to assimilate learning into knowledge.

      Quotes:

      • “What technology does is, it arbitrages time, and you get to live in someone else’s future, which is the most powerful proposition on the planet, and especially what data science enables one to do, is to achieve this at scale.”
      • “One of the main problems in data science and analytics is the adoption of the work, the last mile and being able to have the impact that technology promised.”
      • “It is all logical, and it is all there , so work it out. Technology and data science is logical, it's only about putting our mindset and attitude towards it and working it out. Because everything we do in the tech space is driven by some level of logic, and if its logical it can be done. Don’t accept your own limitation find a way to work around it.”

        • Read the full episode summary here: Episode #131

        Enjoy the show!

        1 hr
      • #130 AI, Ethics and the World of Health Data with Christopher Boone – Global Head of Health Economics & Outcomes Research

        Christopher is the Global Head of Health Economics & Outcomes Research at Abbvie, an adjunct professor at NYU Graduate School of Public Service and active board member of several influential organizations.

        He has received numerous recognitions in the past. In 2019 he was named a Top 100 Innovator in Data Analytics, in 2018 an Emerging Pharma Leader and in 2017 he was a Top 40 Under 40 in Minority Health Honoree by the National Minority Quality Forum

        Christopher explains how, in his eyes, all human data is healthcare data, and how excited he is at the applications this data might have if we learned how to analyze it in a better way, given that, currently, only 5% of all the available data is being analyzed. 

        Stay tuned to know how the broad array of experiences he had in organizations like non profits, government and pharmaceuticals helped him learn to think outside the box and gain a broader perspective.

        Quotes:

        • "I'm just not feeling it, it's just not meaningful to me and I just want to help people.
        • "In my eyes, all data is healthcare data."
        • "I think that the problem that we have is we're still in a society where there's fear of the unknown and I also think that in some cases the system is set up to benefit folks from having a level of fragmentation even lack of data quality."
        • "You also have to identify what is the benefit or value proposition for each of these individuals or groups within the organisation for them to really buy into it."

          • Read the full episode summary here: Episode #130

          Enjoy Christopher Boone in our “Bitesize Insights for Data-Driven Leaders” Series!

          32 min
        • #129 Entrepreneurship Tips from Australian Shark, Steve Baxter – Partner & Investor

          Steve is an investor, a partner at TEN13, and you may also know him as one of the sharks from the show Shark Tank in Australia. His journey in entrepreneurship and investments began over 25 years ago when he started his first company in the telecommunications area. He sold his second business in 2010 and went on to become an investor. Currently, he has an existing portfolio of over 30 companies.

          He was Queensland Chief Entrepreneur for three years, he does mentorships and is also a qualified pilot. Steve has several investments in the US and he draws a comparison between the start-up scene there and in Australia.

          Stay tuned as Steve shares his life experience and provides both tips and inspiration for anyone thinking of starting their own business or already working in their start-up.

          Quotes:

          • “Really bad investments are easy to find… if you can sell to your customers it is a far easier way forward.”
          • “If you're doing it and you know it's wrong, stop it and do anything else.”
          • “The thing about bad news is when you hide it, it just doesn't get any better.”
          • “You're either shooting the lights out or shooting your brains out”


            • Thanks to our sponsor:

            We are Rubix.

            Read the full episode summary here: Episode #129

            Enjoy the show!

            1 hr 4 min
          • Data Futurology Español Ep #1 with Day Manuet

            Felipe Flores es director de data science con casi 20 años de experiencia. Felipe ha trabajado en ingeniería de datos / almacenamiento, reportes, inteligencia empresarial, análisis, data science, machine learning e inteligencia artificial. Actualmente es el Director de Data Science en la empresa de Inteligencia Artificial, Honeysuckle Health.

            Mientras que Day es una experta en data science. Durante 15 años, ha colaborado con corporativos internacionales como Colgate, Gillette, P&G, Walmart y Epworth HealthCare para guiar su estrategia de inteligencia empresarial, de mercadotecnia y decisiones operativas mediante el uso de datos.

            Le apasiona todo lo que tenga que ver con datos e insights, es experta en técnicas cuantitativas, cualitativas y analíticas y ha trabajado con bases de datos, inteligencia de mercados, reportes de datos, ciencia de datos, pronóstico de ventas para innovaciones, machine learning e inteligencia artificial.

            En este episodio Felipe y Day nos dan una breve pero integral introducción a que es Data Science. Platican de cómo desarrollar las capacidades de data science en una empresa y la importancia de la cultura para implementar proyectos de datos exitosos. También nos dan tips de como empezar a desarrollar tu Carrera en Data Science entre otros temas fundamentales de Data Science.

            Temas:

            [03:20] ¿Qué es Data Futurology y ¿cuál es su objetivo?

            [07:30] Trayectoria de Felipe Flores

            [16:30] ¿Qué es Data Science/Ciencia de Datos?

            [19:45] Tips para desarrollar las capacidades de Data Science en una empresa

            [24:10] Sugerencias para alguien que empieza su carrera en data science

            [27:20] Como mantenerse al día en el mundo de data science dado el avance de la tecnología

            [32:30] Cómo especializarse en data science si mi carrera no está relacionada en data science

            [34:10] Entendiendo las diferencias de inteligencia artificial, machine learning, deep learning y data science

            [43:10] Cómo interactúa la Mercadotecnia con Data Science

            [44:35] El rol de la cultura en una organización para implementar data science

            [48:00] Tipos de algoritmos

            [53:50] ¿Qué es la minería de datos?

            [55:30] Libros recomendados para Data Science

            Frases:

            “La idea de un científico de datos es poder mejorar el desempeño de una empresa ocupando datos”.

            “Data science no es una caja de pandora sino hay una explicación detrás de cada algoritmo”.

            “El error más común es que la gente espera terminar el proyecto y decirle a un área que le va hacer el trabajo mucho mejor; la gente que tiene que generar el cambio deben colaborar con la gente de data science desde el principio de un proyecto”.

            “Nadie puede mantenerse al tanto de todo lo que está pasando en data science; es importante entender lo fundamentales de machine learning y estadística y con eso cualquier desarrollo que se de en cualquier área y así cuando necesitas aprende en cualquier área”.

            “En general el conocimiento depende de la persona cuando uno se quiere exigir y esforzarse; el conocimiento existe lo más importante es practicar poner los conocimientos en práctica”.

            “Uno puede tener los planes más espectaculares, pero si la cultura no existe nada va a funcionar; la cultura es el ingrediente más importante de data science”.


            Join Data Futurology on Telegram: https://t.me/datafuturology

            Únete a Data Futurology Español en Telegram: https://t.me/df_espanol

            YouTube: https://www.youtube.com/watch?v=WRop1cfFVo8&t=135s 

            1 hr 5 min
          • #128 A Global Perspective on the Future of Data, Disruption and the CDAO Roles with Pieter Vorster – GM CSR & Chief Data Analytics Officer

            Pieter Vorster is the GM CSR & Chief Data Analytics Officer at Commonwealth Bank, one of the largest companies in Australia. He is an international recognized leader in the data analytics space with over 20 years of experience in industries like retail, wealth, corporate and investment banking, financial services, insurance, etc.

            He talks about how disruption within the organizations, though sometimes avoided, is necessary to create better solutions for the customers. He believes a key guiding principle should be to benefit the client, and that transforming strategies and technologies can only take place at the same pace as social transformation.

            Stay tuned to learn more about Pieter’s exciting journey and his ability to combine customer perspectives with data, AI and digital business models in a unique and effective way to get results for organizations.

            Quotes:

            • “The moment you need to get agreement from everyone, mediocrity around consensus will apply”
            • “If you’re just trying to move money from one part of the business to another part of the business you’ll never succeed”
            • “The banks have got lots of data, lots of toolsets, people just don’t know how to use them”

              • Thanks to our sponsor:

              We are Rubix.

              Read the full episode summary here: Episode #128

              Enjoy Pieter Vorster in our “Bitesize Insights for Data Driven Leaders” Series!

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              Send in a voice message: https://anchor.fm/datafuturology/message
              39 min
            • #127 Reinventing Prostate Cancer Testing with AI: From Development to Regulation to Production with Elliot Smith – CEO & Founder

              Elliot Smith is the CEO and founder of Maxwell Plus. A visionary company that has been using machine learning and artificial intelligence to help treat and diagnose patients with prostate cancer. The way they bring in the data, help analyze it and help people along their journey is fascinating and makes them leaders in this specific field.

              Elliot is very passionate about helping others find diseases at a point where they can be treated. To know where things are, if they should be treated and how best to treat them is his ultimate goal in terms of applying data science and AI to the medical world.

              Stay tuned to know how his desire to build something that could be useful in the real world turned into a company with the potential of impacting the lives of over 300 million men that have or are being diagnosed with prostate cancer.

              Quotes:

              • When I finished that I sort of came to the realisation that I loved academia, but it was a little bit too slow moving for me. I wanted to be out there building things, putting stuff out into the world and decided to have another run at building a start-up and at the time I happened to know a lot about numerical modelling, optimisation and how that translated into things like AI and also medical imaging and without jumping too far ahead that's the point where all of this came together and the company that I now run Maxwell plus was born in that collision of worlds.
              • We looked at their data, we saw something in their data that wouldn't have been picked up otherwise and our doctors said we need to act and with the hindsight of knowing their outcomes we acted at the right time and those people have what is for prostate cancer is 98% 5 year survival rate because we acted in time to avoid that conversation.
              • If you have had treatment or you choose to go into what is called active surveillance, which is let’s just watch this and determine when to treat, the algorithm that we apply to do initial diagnosis apply just as well to monitoring your diagnosis over time. How can we then go to provide ongoing support to really see these men through from day one to day infinity and continue to provide real clinical value to these men.

                • Read the full episode summary here: Episode #127

                Enjoy the show!


                1 hr 2 min
              • #126 Data-Driven Approaches From Politics to Aerospace with Adam Bonnifield – VP Artificial Intelligence

                In episode 2 of our “Bitesize Insights for Data Driven Leaders” Series, Adam Bonnifield is a VP of Artificial Intelligence at Airbus. He is a former Chief Product Officer (Census) at the U.S. Department of Commerce and Co-Founder of Spinnakr and Giv.to. Adam lives and breathes online engagement - he ran digital strategy for political campaigns since he was in college, breaking Congressional fundraising records. After graduating from Cambridge University, he was awarded the Tsuzuki Fellowship to direct online youth outreach in Japan.

                Enjoy Adam Bonnifield in our Bitesize Insights for Data Driven Leaders” Series!

                Quotes:

                • “Don’t talk so much when you’re the boss. Just stop talking so much about stuff.”
                • “You have a sort of natural optimism because you have the experience of building something from nothing. And realizing that anything can be done, especially in data technology. At the same time, you’re a child when it comes to navigating corporate politics.
                • “I was the kid that went to the Aerospace Museum every week. I am in love with aircraft. When you work with a company with a specialized product, you’re surrounded by people with a patriotic feeling for what they do.”
                • “It was a special time because it wasn't really known what you could do with data.”
                • “If you're working in data science, I would look for companies with complex supply problems."
                • “We need a new paradigm of data storytelling and data visualisation built for regular people.”


                  • Read the full episode summary here: Episode #126

                  Enjoy the show!

                  42 min
                • #125 Transitioning From Academia to Business – The Skills Gap with David Hardoon – Senior Adviser for Data and Artificial Intelligence

                  David is the Senior Advisor for Data and Artificial Intelligence at UnionBank Philippines. Concurrently David is an external advisor to Singapore's Corrupt Investigation Practices Bureau (CPIB) in the capacity of Senior Advisor (Artificial Intelligence) and to Singapore's Central Provident Fund Board (CPF) in the capacity of Senior Advisor (Data Science).

                  David loves the idea of programming logic. We have the ability to use information as mechanisms to assist us on a day-to-day basis. So, David was inspired to explore the possibilities of data. After high school, David considered artificial intelligence or astrophysics. However, he ended up finding a place that has a combined degree of computer science and artificial intelligence. In fact, he was the second student to complete the degree.

                  Stay tuned as David gives his perspective on data governance – it's a mechanism that allows us to identify what we should and shouldn't do. In addition, David reveals his views on AI governance, and David explains how he balances all of his work.

                  Quotes:

                  • “I was called a geek many, many times in my life, so I’m going to own it now.”
                  • “The objective is: how do you take these very complex ideas, and explain them in very pragmatic, very relatable terms.”
                  • “I personally have a bit of an aversion to the term [data scientist], for two reasons: every scientist uses data, and it’s just too generic.”
                  • “We need to also equally realise when data isn’t relevant, … a process is what’s required.”

                    • Read the full episode summary here: Episode #125

                    Enjoy the show!

                    55 min
                  • #124 The Data Science Team: Skills Needed, Purpose and How to Structure with Dan Costanza – Chief Data Scientist

                    Dan Costanza, Chief Data Scientist at Citi, joins me for the first episode in the new “Bitesize Insights for Data Driven Leaders” Series. Dan opens the show by explaining how he got interested in data. After graduating from college, Dan went into an investment banking role. Eventually, he received an exciting project that got him started down the data path. Dan says as someone who didn’t study computer science in school, it has been a heavy lift trying to get those technical skills up to par. During a code-heavy project, Dan needed to learn how to break up the project and work through it. Also, he learned how to think about sampling data without bias.

                    Then, Dan explains the importance of emotional intelligence for data science. Conscientiousness and emotional intelligence are the things that you can actually interview for. Instead of judging people on their grades, we need to judge people on their ethics, communication skills, and willingness to work in teams. In India, Dan set up a data science team. The talent in India is insane. However, there are cultural differences Dan needed to work through. For instance, he told his team that they needed to speak up when they had ideas. If you create space for people to bring their own thoughts, you’ll hear loads of good suggestions. Before Dan told his team that, they would withhold useful information.

                    Quotes:

                    • “When you look at the hiring research again, like there are two real categories and the one is things you don’t interview for, which are the intellectual horsepower things and those are - how smart you are, do you have some specific skills I need. The word that always comes up on the other side is conscientiousness, and that encompasses the stuff we talked about at the beginning, and the emotional intelligence, teamwork parts of it and those are the things you do actually interview for. Which is counterintuitive for a lot of people who work in quanti type roles because you want to ask people really hard questions, to see if they are smart, but the problem is the data doesn’t support that as being predictive of anything when you control for their grades.”
                    • “You start by spraying things around, working with a lot of people, just to get the volume in and see who those people are and meet people, and as you work a little bit, you start to understand their own types of workflow.”
                    • “More powerful then compliant is having good ethics there on the ground.”


                      • Read the full episode summary here: Episode #124

                      Enjoy the show!

                      31 min
                    • #123 Why We Need to Focus on Implementing Data Governance with Michelle Pinheiro – Head of Enterprise Data Governance

                      Michelle is Head of Enterprise Data Governance at ANZ Bank. In this role, Michelle is responsible for Data Governance strategy across the group, ANZ Data Privacy and Ethics framework, Enterprise Metadata Management, Data Risk and a Centre of Excellence for Data Quality. Michelle has over 25 years of experience in the world of Data and utilizes that knowledge to help foster organized and sustainable large scale analytical environments for commercial success. Michelle has a particular interest in building frameworks for ethical data use by successfully developing ANZ’s principles for Data Ethics.

                      In this episode, Michelle describes the importance of transparency in data ethics. For instance, in the world of insurance, people want to know how their premium is calculated. What information is the company using to calculate the insurance premiums? So, the insurance company needs to explain what information they are putting into the black box. Insurance algorithms for premiums are like the formula for Coca-Cola; no one ever shares it. To combat this, Michelle needed to put herself in the mindset of the customer.

                      Stay tuned as Michelle explains how the customer journey can benefit from data governance. Also, Michelle reveals where she thinks the future of data ethics is going, how data ethics overlaps with data governance, and the ways that consent fits into data ethics.


                      Quotes:

                      • “I did a lot of work in redesigning documents and determining what information to disclose and that really comes down to transparency and transparency is a big aspect of data ethics.”
                      • “That was a legislation where you actually had to articulate what are the factors, what is the information that you give us that we actually then use to calculate your premium. So it took it from being an enigma to explaining these are the inputs that we put in. And that's got a lot of relevance to today's world with artificial intelligence which is what information are you putting into that black box to then produce the outcomes that are going to impact me. And so I guess that's the genesis of it and that was a really big change in the insurance world because insurance algorithms for premiums are like the formula for Coca-Cola nobody ever shares them anywhere.”
                      • “I'm not shy about saying you know data is not part of the IT world, it's part of the business world.”

                        • Read the full episode summary here: Episode #123

                        Enjoy the show!


                        1 hr 2 min

                      About Data Futurology - Leadership And Strategy in Artificial Intelligence, Machine Learning, Data Science

                      From the publisher's feed

                      Artificial intelligence is a tremendously beneficial technology that's advancing at an incredibly rapid pace.