AI Data Privacy – What You Should Know!

Date | Time
March 13, 2019
6:30PM – 8:00PM

Location
Galvanize
303 Spring Street
New York, NY 10013

(Event Video by Kenneth Kraetzer from CBSI Services)


In our modern world of technology and artificial intelligence (AI) your personal data and freedom of privacy is being affected. With the constant collection of self-governing tech systems, connected devices/machines, smart phones/homes, and drones your personal data is being collected, tracked, and used by all types of companies. Can real-time decision-making by self-governing tech discriminate and restrict you of choice or possibilities? How safe and private is your personal data from hackers? Is a data profile being built of you? What type of data privacy protection safeguards are there for citizens? We will explore this and more in this very important session on data privacy in the era of modern technology. The right to privacy is the fabric of humanity and that must be protected.

Speakers:

Xena Ugrinsky  
CEO of GenreX Consulting, a strategy consultancy specializing in business performance optimization through data science. She provides strategy and client advisory related to implementing data science and addressing the challenges of evolving in an age of AI. 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. Before that, Ms. Ugrinsky was a partner at KPMG’s US Advisory practice. Most recently, she authored the book “Enterprise AI – Your Field Guide to the New Business Normal”, which discusses how to drive data science initiatives, provides a methodology for adoption, and considerations for making them take hold at the enterprise level.

Jennifer Shin
Jennifer Shin is the Founder of 8 Path Solutions, a data science, analytics, and technology company based in NYC. She is internationally recognized as a thought leader, influencer and expert in data science, business, and technology by corporations, governments, and academic institutions. A seasoned data scientist and management consultant, Jennifer has successfully implemented complex, large scale, and high profile projects as a Product Director at NBCUniversal, Director of Data Science at Comcast, Senior Principal Data Scientist at The Nielsen Company and Management Consultant at GE Capital, the Carlyle Group, Fortress Investment Group, the City of New York, and Columbia University.

Raz Choudhury
Raz Choudhury is the founder and CEO of SAM. Raz oversees all aspects of the company’s strategic goals and works closely with the product development team to achieve SAM’s long-term vision. Raz started his career at age 19 as an Engineer at IBM. Raz spent six years leading IBM’s major Northeast accounts such as Goldman Sachs, Mitsubishi International Trading, and AXA Equitable. Raz’s numerous professional certifications, as well as broad expertise in internet technologies, drove him to strike out on his own. In 1999, Raz founded and ran USAWeb® – now Office Interactive® – an award-winning app development and lead generation technology company based out of New York City.

Reid Blackman, Ph.D.
Founder and CEO of Virtue, a risk management consultancy firm. Reid was gripped by ethical problems the first semester of his first year in college over 20 years ago. Countless hours later, after reading, arguing, and teaching about ethics, he’s still hungry for more. While his early research concerned issues largely contained within the ivory tower, his research has become increasingly action-orientated, particularly as it concerns the ethics of institutions like governments and corporations, and also the ethics of emerging technologies.

Sponsors:

Galvanize
Galvanize is a dynamic learning community for technology. Our community is where people and companies with the guts and smarts to create real-world change congregate and inspire each other. Our goal is to make opportunities in technology available to all those with the aptitude, determination, and drive.

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Finding AI Solutions for Algorithmic Fairness

Date | Time
November 1, 2018
6:00 PM – 8:00 PM

Location
Amazon AWS
7 W. 34th Street
New York, NY 10001

(Event Video by Kris Skrinak of Amazon AWS)

Event Abstract
Join Artificial Intelligence Hub and Amazon AWS for an algorithmic fairness event. In our modern world of artificial intelligence/machine learning many companies, government agencies and hospitals are relying on algorithms and data to predict credit worthiness, preferred treatment for illnesses, job interviews, parole, and much more. As the evolution of machine learning continues to advance, having a better understanding of how to develop algorithms that are fair will become extremely important. Many current proprietary algorithms could have biases in the data or models that can potentially impact or have severe consequences in society.

Fortunately, many brilliant researchers and data scientists have started to look for solutions to address this difficult challenge. Join us for a serious discussion with expert Data Scientists and Researchers from IBM, Microsoft, NYU, and AI For Good Foundation that are working on finding solutions and to implement more oversight when developing specific algorithms and machine learning products.

Speakers

Claudia Perlich
Claudia Perlich is a Senior Data Scientist at Two Sigma in New York City. Prior to her role at Two Sigma, she was the Chief Scientist at Dstillery where she designed, developed, analyzed, and optimized machine learning that drives digital advertising to prospective customers of brands. She started her career in Data Science at the IBM T.J. Watson Research Center, concentrating on research in data analytics and machine learning for complex real-world domains and applications. She tends to be domain agnostic having worked on almost anything from Twitter, DNA, server logs, CRM data, web usage, breast cancer, movie ratings and many more. Perlich is a very active public speaker and has published over 50 scientific publications as well as a few patents in the area of machine learning. She received her PhD in Information Systems from the NYU Stern School of Business and holds a Master of Computer Science from Colorado University.

Eric Schles
Eric Schles works for Microsoft as a Data Scientist and also works as an Adjunct Professor and researcher at NYU. He specializes in using big data to combat human trafficking. Eric has worked for the Manhattan DA’s Human Trafficking Response Unit, serving as Senior Analyst and for the White House under the Obama Administration in the past. He is deeply passionate about solving slavery and using data science and automation to do it. His research at NYU is focused on combating human trafficking.

Karthikeyan Natesan Ramamurthy
Karthikeyan Natesan Ramamurthy is a Research Staff Member in IBM Research AI at the Thomas J. Watson Research Center, Yorktown Heights, NY. He received his PhD in Electrical Engineering from Arizona State University. His broad research interests are in understanding the geometry and topology of high-dimensional data and developing theory and methods for efficiently modeling the data. He has also been intrigued by the interplay between humans, machines, and data, and the societal implications of machine learning. He is a key contributor to the open source AI Fairness 360 toolkit. His papers have won best paper awards at the 2015 IEEE International Conference on Data Science and Advanced Analytics and the 2015 SIAM International Conference on Data Mining.

Manojit Nandi
Manojit is a Senior Data Scientist for Rocketrip. He has previously worked at Informed.co, STEALTHbits Technologies, and Verizon Wireless as a Data Scientist. He was a fellow in the 2013 Data Science for Social Good fellowship where he became interested in using his data science skills to solve challenges with high societal impact.


Artificial Intelligence Marketing Beyond The Hype!

Date | Time
April 9, 2018
6:30 PM – 8:30 PM

Location
IBM
Fat Cat Fab Lab
224 West 4th Street
#250
New York, NY 10014


Join Artificial Intelligence Hub and find out all about Artificial Intelligence Marketing and how it can help grow your startup or small business. We are partnering with IBM’s Fat Cat Fab Lab and we are grateful to be hosting our AI marketing event there.

Artificial Intelligence/machine learning is here to stay! Whether you are launching a startup or want to implement some elements of AI marketing into your existing campaigns this presentation will help you get started. AI/machine learning is being implemented across every industry and by every major organization throughout the world. We are able to solve incredible challenges by utilizing AI algorithms unlike ever before. The same is true about marketing and advertising, you can get to know your customers with an unprecedented level of detail and give them a unique personalized customer journey and experience.

With machine learning and deep learning algorithms you can have access to unlimited data, customize search and recommendation engines, improve customer segmentation and programmatic advertising, create intelligent email content, and even use chatbots to create content and websites. Learn how to maximize your marketing efforts and put machine learning and deep learning algorithms to good use.

About the speaker:

Ana Valdes, Founder of Artificial Intelligence Hub (AIHub) and Ana Valdes Consulting is a seasoned marketing leader with unique background in graphic design, Python programming, and machine learning. She has over 18 years of experience in creating and executing marketing frameworks, plans, and strategies that produce growth results and brand recognition for large and small companies. Ana has provided both marketing and design services to brands such as: NASA, Whirlpool Corporation, K&L Gates, GW Medical School, University of Miami, SAM.ai, WeightLess, Friends of Lafayette Park, and many more. Ana develops and designs AI marketing workshops to educate students on the value of AI in business growth. She has also developed AI events and has partnered with Amazon and IBM to bring leaders to discuss topics such as: ethics and privacy, algorithmic fairness, cybersecurity, and AI for marketing.

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