Ethics, Bias and Things That Go Bump in an AI Night
Award-Winning Author, Speaker, Future Trends Expert, and VP of Big Data Cognitive Systems at IBM
- Offers a framework for excelling in a time of rapid change
- Explains why Big data, AI, data science, deep learning, and machine learning are not just a competitive edge but survival tools, and how to capitalize on them
- Discusses evolving technology issues including the implications of AI as it relates to ethics, bias, and transparency
- Presentation full of energy, humor, and incredible visuals used to demonstrate the power of analytics, including live demonstrations of what’s talked about in action
In a rapidly transforming world, data has become the new competitive advantage. And according to future trends expert Paul Zikopoulos, “Every day we walk by solvable problems, leaving opportunities untapped.” The VP of the Big Data Cognitive Systems for IBM, Zikopoulos discusses how working these “solvable problems” creates disruption in the marketplace and how golden signals of opportunity can be found within mountains of noise. Exclusively represented by Leading Authorities speakers bureau for lectures, Paul is changing the way audiences are looking at their businesses in terms of potential sales, obstacles, and potential for growth. Paul shares future trends that are starting to happen in real-time and have multiple applications: from garbage cans that alert sanitation departments when they need collection – saving cities millions – to shampoo brands that are connecting weather forecasts with personal consumer profiles to suggest the right mix of hair products for the day. He easily discusses the next generation of technological change from the power of machine learning and voice-to-text, to the opportunities in reading digital body language and joining the Internet of Things trillion sensor economy, and more.
Incredibly energetic and easy to follow, Paul is the antithesis of what many people think of when they consider a big data expert. Using incredible visuals, including a hashtag aggregator that instantly creates examples of perfectly segmented consumers live on stage, Paul amazes audiences with the amount of information available to change the conversation about your industry. By sharing his insights on where big data comes from and the idea that “If you aren’t paying for it, you are being sold,” Paul breaks apart the roles of data collection and decision making for executives seeking the opportunities for disrupting their industry and leap-frogging the competition.
Named a “Top 100 AI and big data Thought Leader” by Analytics Insights and one of the “50 Big Data Twitter Influencers” by SAP, Paul has been consulted on these topics by “60 Minutes” and multiple universities, and has been named an expert on big data by publications such as Big Data Republic, Technopedia, and Analytics Week. An award winning writer, he has published more than 19 books and over 350 articles on data including Big Data Beyond the Hype, Understanding Big Data, Harness the Power of Big Data, DB2 for Dummies, and more. An expert in harnessing the power of big data, Paul brings real world experience from his at time managing over 1,400 professionals to help you build influence and affect change in your company.
Paul also is a seated board member of Queen’s University Business School’s Masters of Management Analytics (MMA) and AI programs. Paul has taken an active role in bolstering Women in Technology, LGBT and workplace inclusivity, and Coding for Veterans. He sits on the board of Women 2.0, a global network and social platform for aspiring and current female founders of technology ventures.
The Big Deal About Big Data. Is there a more frequently used term than Big Data these days? It’s changing the world, but we don’t yet know how it will sell, operate, learn, heal, and determine big decisions. In this session audiences get a quick framework by which to identify and understand Big Data (hint: it’s more than Tweets and Facebook “likes”), and how it’s being used across industries to transform the norm. In addition, get insight into what modern analytic architectures look like—you’ll hear about governance, data lakes, snow flakes, and more. Zikopoulos will leave you with not only a great understanding of Big Data, but also how you are going to change the world with it.
Future Tech Trends. Today’s competitive advantage lies in data. Everyday we walk by solvable problems, leaving opportunities on the table. According to big data expert Paul Zikopoulos, it is exactly these kinds of solvable problems that disrupt industries and create new businesses. In his presentation, Paul outlines the forces driving innovation and discusses how technologies from machine learning to cloud computing will shape the future and how social, mobile, and the internet of things will change how we interact with businesses and each other.
Women in Technology. Spoiler Alert: Paul is male. But the advancement of Women in Technology is one where men must be allies. After managing and growing hundreds of careers first hand, Paul brings an entertaining and insightful point of view into women in technology with sound advice on how to build confidence, grow personal careers, and pay it forward.
Internet of Things. From milk cartons with temperature controlling tags to tee-shirts that monitor the vitals of post-operation patients after they leave the hospital, the merging of technology and data is taking consumers into the future of tech. Paul discusses the profound effects of this new technological frontier and teaches audiences where their business model can benefit from new applications of data.
Disruption. In a world where Facebook is the biggest media company but creates no content, Uber is the largest taxi service but owns no cars, and AirBnB is one of the most popular places to book a place to stay but owns no buildings, data is the new competitive advantage. Paul breaks down the main business factors disrupting the marketplace and what you can do as a business to succeed in such a time of change. Paul then goes one step further to predict the industries ripe for disruption and identify potential new products that will change the way we work and live.
Monetization of Data: Data Collection is 24/7 but Decision Making is Not. Most consumers and businesses may not realize that if you are not paying for it, you are probably being sold. Paul uses live examples from twitter to show how much data is readily available and how quickly statistics from one hashtag can be used to segment a market and create a potential consumer profile. Paul pulls from current case studies to explain how unlikely business partnerships can be the most profitable and strategic when capitalizing on data.
Leadership and Career Building From Mentor to Mentee. As a recognized top mentor at IBM, and a leader of organizations from 10 to well over 1,000, Paul brings over 21 years of experience, stories, and frank observations into building teams, careers, how to mentor, what makes for great leadership, and the kinds of people to never be (or work for). This energetic talk is all about transferring energy from stage and into your teams.
The Power of STEM. Science, Technology, Engineering, and Math (STEM) skills are the currency of the future. Sadly, our continental market place isn’t equipping itself at the rate of innovation needed. STEM paths start much earlier than anyone think: Indeed, youth are making pivotal decisions in Grade 4 that place them on a path. In high school there are more key decision points around STEM skills. Paul uses his unique ability to ‘connect’ with youth with an invigorating talk that can be tailored from Grade 4 to high school students and the power of STEM.
Unstuck: How to Foster Personal Career Growth.
Ever feel stuck, and can’t figure out how to turn around? The definition of stuck will vary, some of you will be stuck in a “3rd World” way and that’s serious; some of you will be stuck in a “Champagne” way, and guess what, that’s serious too. It’s all relative. And while you can’t have “Champagne” stuck if you have “3rd World” stuck (consider yourself lucky to be “Champagne” stuck!), stuck is still, well, stuck.
I’ve been stuck my whole life. You know why? Spoiler alert: I’m human. The death of my first child, Grace, still leaves me stuck. I’ve been work stuck more times than I can remember. Over the course of your career, you should expect to feel stuck. Those gears are going to stop spinning fast and you’re going to have to replace some parts. If you’re not actively maintaining that engine, it’s no wonder why it’s stuck. It’s a fact: people and things get stuck – in relationships (friends and significant others), work, life and so on.
The position of stuck, as external of a force as it seems, ironically starts from within. And I can tell you that almost every single major professional accomplishment I’ve achieved was from the position of stuck. The stories behind finishing my MBA, becoming an award-winning and professional writer/speaker, getting approached by the TV show 60 Minutes or called out on The View, getting involved with Women in Technology, any highlight I could share in my 23 years came from the position of stuck.
It’s the “how I deal with stuck” that created an avalanche of professional accomplishment, at least for me. This talk is about career stuck. I’m going to share with you strategies to get un-stuck, and the things that, every single time, over any accomplishment I’ve had, were present.
Remember this: you’re not a tree. If you don’t like where you are, you can move. Ready to get things moving? Let’s get unstuck!
Trust, Ethics, and Bias - Eventual Inertia and Things That Go Bump in an AI Night
No questions about it, AI is creeping up everywhere these days. If we accept that AI is going to be a relevant part of our future, it's important to establish the foundations of trust in AI systems. Why did this person get denied for a loan and that person didn’t? What data was used to create sentencing guidelines? Will our company use AI to be good actors of society or bad ones? (News headlines make this one self-explanatory.) With AI comes great responsibility.
There is an old Canadian hockey saying “Don’t go to where the puck is, go where it’s going to be”. Trust, ethics, and bias isn’t getting as much attention (outside of research) as it should … but with regulations such as GDPR and the ubiquitous headlines of data lost or mis-used … this the big discussion you have be having (or will soon be forced to have) in the board room as you plan out your AI strategy or evolve it. (Spoiler alert: conversations had before you are forced to have them always put you on a faster path to success, mitigate costs, and separate you from your peer groups.)
In this session you’ll learn about a framework for build trust into AI. You’ll understand bias and how it can influence models, and how to spot bad bias and acceptable bias as well. You’ll learn about explainability, its effect on society, and more so how it can help infuse AI "take rates" across the business. In short, you’ll be where the AI puck is going to be.
Bottom line: You need AI that is transparent so we can inspect the algorithms to make sure they’re doing the right things and just like how early automobiles didn’t always drive straight, have seat belts, or window wipers (all safety mechanism), our early AI algorithms are going to need bumpers for safety.
(Note: this is a great follow up session to my keynote “The Mysterious World of a Thinking Business” where you hear about these concepts, see them in action, and their use cases … or the this is the “How It Works & Your Rightful Seat at AI Table”).
How It Works & and Your Rightful Seat at AI Table
How does Alexa know most of the time what you are saying? How does a computer find a face in a picture and then magically tells you who it is? (It starts the same way your camera puts that yellow box around a face when it's ready to take a picture.) How can a computer convert English into Spanish (or almost any language for that matter) with accuracy that puts to shame 20 year old expert made translation systems? How can a computer read an online review and come up with a rating? Or how does it seemingly understand a passage of text with respect to who, where, what, when, and more?
I’m not a data scientist (presumably neither are you). I have no plans to be a data scientist. I think data science is interesting and I want to learn more about it. MOST OF ALL I wanted to know when data scientists (or anyone for that matter) are talking around me so they could go off and do their next project. After all, I owned the business, I needed to have an understanding … I needed to keep my seat at the "AI Game of Thrones Table" and thus I set out to learn how this stuff works.
In this interactive presentation, the audience votes in real-time what they want to hear about and how it works. Not a techy? Even better, words such as ‘back propagation’ and ‘morphological operations’ have been banished from this talk so the every day person can see how stuff is done behind the scenes.
Packed with lives demos and some fun, you’ll leave this session with a sound understanding of the “How of AI” and up your game in strategic conversations around the AI strategy for your enterprise.
(Note: this is a great follow up session to my keynote “The Mysterious World of a Thinking Business” where you hear about these concepts, see them in action, and their use cases … this is the “How”).
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Paul. Thanks for coming to New Orleans! You were tremendous! We need to explain this relationship for the entire profession, I believe this has started that process.
I received post positive and negative feedback. The positive was that your session was great. The negative was that I should have booked you for longer. Certainly a mistake on my part ... thanks for everything.
Thank you again for participating at the Global Forum last week! Your presentation was very well received and the real highlight of our event for attendees.
Thank you again for a wonderful presentation at our Annual Conference … The audience LOVED it.
I wanted to reach out to you to personally thank you again for speaking at our event last week … I’ve received some really great feedback and appreciate you taking the time to educate us
You did a great job. The buzz for the rest of the day around your talk was perfect - we couldn't have asked for a better speaker or message. The audience loved and was intrigued by every piece of your talk.
Your presentation was best described as "mind blowing" and has sparked new ways of thinking. The highest rated component of our Director program, your talk has helped with a cultural shift ... and our thinking around Big Data.