The Future of Work executive event presentation by Ross Dawson.
When you inspire your workforce to innovate and collaborate, you create tangible business value.
The winning organisations in a hyper-connected world will be those that create many opportunities for their workforce to interact with each other and ‘the outside world’ at scale.
Today’s successful and sustainable businesses all have one thing in common – they have engaged, happy workforces in which the majority are Contributors
Data Science can bring scientific rigor to an organization’s decisions and processes. However, empiricism often fails to properly account for social norms, human relationships, and phenomena that have yet to manifest themselves in data. This is where intuition, cultural values, gut feel, and judgment—or “art”—still provide value to decisions. There is a class of problems that calls for precisely the combination of art and science. For social products—such as books, music, video, and apparel—focusing on either art or science at the exclusion of the other will lead to less than optimal results.
For years now we’ve espoused data-driven decision making into the organization. While we still need to take this further, there is equal opportunity in internalizing the “art” that exists within the organization. The judgment and cultural values that reside within the brains of our employees can be harvested and married with data science to produce new capabilities. In this talk we will share new ideas about how to systematically combine the assets of the organization—be they people or machines.
The Future of Work executive event presentation by Ross Dawson.
When you inspire your workforce to innovate and collaborate, you create tangible business value.
The winning organisations in a hyper-connected world will be those that create many opportunities for their workforce to interact with each other and ‘the outside world’ at scale.
Today’s successful and sustainable businesses all have one thing in common – they have engaged, happy workforces in which the majority are Contributors
Data Science can bring scientific rigor to an organization’s decisions and processes. However, empiricism often fails to properly account for social norms, human relationships, and phenomena that have yet to manifest themselves in data. This is where intuition, cultural values, gut feel, and judgment—or “art”—still provide value to decisions. There is a class of problems that calls for precisely the combination of art and science. For social products—such as books, music, video, and apparel—focusing on either art or science at the exclusion of the other will lead to less than optimal results.
For years now we’ve espoused data-driven decision making into the organization. While we still need to take this further, there is equal opportunity in internalizing the “art” that exists within the organization. The judgment and cultural values that reside within the brains of our employees can be harvested and married with data science to produce new capabilities. In this talk we will share new ideas about how to systematically combine the assets of the organization—be they people or machines.
Top #AI,#Data and #Analytics posts of the week. Thanks for the likes, comments and shares! Have a great week...and be #AIDriven!
[Shout Out] to David Sym-Smith for sharing #motivation #quotes. My top 5 @ https://bit.ly/3dlKCJ4
[Research] #Only 14.6% report to have deployed AI into widespread #production. Great #research piece by Tom Davenport and Randy Bean @ https://bit.ly/398Kr0n
[Secrets] of Exceptional #Leaders. 4 things they do @ https://bit.ly/2U8sA5E via Mike Quindazzi
[Communicate like a #boss] 21 things you must do via Dia Bondi.
[Trends] #Innovation and #Automation with Julian Dontcheff @ https://bit.ly/33BeTPR
This update ‘broke the internet’ this week (-> https://bit.ly/3beb1GQ).
All weekly updates from the last 30+ weeks can now be found @
Be #AIDriven and see you next week!
Here are a few prominent female inventors who deserve to have their names stay with us forever, along with their remarkable endeavors to advance technology and our everyday lives.
This Friday Shift is a conversation with Marlies van Dijk about leading during these troubling times: dealing with fear, adding value, and how to raise uncomfortable topics.
3 reasons you can't avoid social media (even if you want to) series The Social Executive
Even if you want to avoid social media you can’t. Its pervasiveness & power to reach global audiences instantly creates dramatic impacts.
Here are 3 reasons you can’t ignore it.
1. You can be drawn in
2. People in your business use it
3. The law says so
This is the first in a series of presentations that looks at why you're already in social and gives you a list of important questions to ensure you, your Board and executives know how to answer.
Keynote Slides: Profiting From Technology TrendsRoss Dawson
Slides for Ross Dawson's keynote at National Association of Federal Credit Unions Board of Directors Conference in Maui. Slides were designed to support the keynote, not to be viewed alone. For more see www.rossdawson.com
Centralize OR Decentralize?! Eliminate Decision Failure & See The Future…
From Data to Analytics and Decision Making, new practices to help you succeed today and tomorrow.
One Person's Link Bait is Another Person's News: Understanding Generational C...Michael Leis
Between boomers, Generation X, Millennials, and Generation Z, there are lots of accusations thrown around. But here I take a look at how distinctly each generation approaches technology. I start with understanding the technology people had when they were 14, and apply that through quantitative and qualitative data to unlock trends that help us empathize with the unique qualities of why these generation understand systems and technology so differently.
Dreamforce 2015 - Hack the Tech WorkforceMary Scotton
It's been over a year since Silicon Valley tech companies published their dismal diversity stats, showing the low number of under-represented minorities and women in tech. In response, we've seen a growing community of entrepreneurs and programmers hacking the tech workforce, one hackathon/conference/company at a time. Join us to hear their stories and learn how to implement these hacks in your workplace.
Recording: https://www.salesforce.com/video/192778/
Strata Conference NY: The Accidental Chief Privacy OfficerJim Adler
Strata Conference
New York
September 23, 2011
http://strataconf.com/stratany2011/public/schedule/detail/21484
http://youtu.be/PKUI9iz0l9g
The first generation of chief privacy officers were typically attorneys, charged with the formulation and enforcement of privacy policies. Times have changed. Given the speed and complexity of technology, the privacy policy is necessary but hardly sufficient. Because we live much of our lives in public, both online and offline, the Internet is transforming the anonymity of our cities into the familiarity of small towns. Privacy is deeply ingrained within the technology that manages this personal data. The products and services driving this transformation must consider privacy from the earliest design sessions.
Today’s engineer CPO, and I’m one, must deeply involve themselves with the technology and product design process to bake-in privacy. This new breed of CPO is comfortable in an engineering scrum, product focus group, reviewing pending regulations, or analyzing A/B test results. They have the historical awareness, frontier spirit, regulatory caution, technical chops, and innovator’s curiosity to work through the toughest data issues. The promise of the engineer CPO is that products, not only safeguard privacy, but compete on it.
Speaker Slides: Bringing Agile Management to International DevelopmentMorgan Johnson
Speaker slides from the workshop Bringing Agile Management to International Development hosted by OnFrontiers in Washington DC, July 16, 2019 at the Eaton Hotel.
O'Reilly TOC: A Social Approach to PublishingOpenMatters
Presented at O'Reilly Tools of Change Conference as Key note presentation to publishers to help them better understand the value of social media as part of their e-initiatives.
Machine Learning and/or AI is being adopted across many industries at a rapid pace. But Bias in AI, lack of talent diversity in AI and lack of access to knowledge pose major risks. In this presentation, I showcase some real-life example of Bias in AI. But if we take the right steps we can build an Inclusive AI. Building an Inclusive AI is the right thing to do for the society, it also makes for a great product and business.
This talk is divided in 3 parts: inspiration to study; the business aspects of Artificial Intelligence; and its technical aspects, with a practical demo and technical explanations about Overfitting, NN, CNN, PCA and feature extraction. The code used during the demo will soon be on Github.
Talk on Algorithmic Bias given at York University (Canada) on March 11, 2019. This is a shorter version of an interactive workshop presented at University of Minnesota, Duluth in Feb 2019.
Top #AI,#Data and #Analytics posts of the week. Thanks for the likes, comments and shares! Have a great week...and be #AIDriven!
[Shout Out] to David Sym-Smith for sharing #motivation #quotes. My top 5 @ https://bit.ly/3dlKCJ4
[Research] #Only 14.6% report to have deployed AI into widespread #production. Great #research piece by Tom Davenport and Randy Bean @ https://bit.ly/398Kr0n
[Secrets] of Exceptional #Leaders. 4 things they do @ https://bit.ly/2U8sA5E via Mike Quindazzi
[Communicate like a #boss] 21 things you must do via Dia Bondi.
[Trends] #Innovation and #Automation with Julian Dontcheff @ https://bit.ly/33BeTPR
This update ‘broke the internet’ this week (-> https://bit.ly/3beb1GQ).
All weekly updates from the last 30+ weeks can now be found @
Be #AIDriven and see you next week!
Here are a few prominent female inventors who deserve to have their names stay with us forever, along with their remarkable endeavors to advance technology and our everyday lives.
This Friday Shift is a conversation with Marlies van Dijk about leading during these troubling times: dealing with fear, adding value, and how to raise uncomfortable topics.
3 reasons you can't avoid social media (even if you want to) series The Social Executive
Even if you want to avoid social media you can’t. Its pervasiveness & power to reach global audiences instantly creates dramatic impacts.
Here are 3 reasons you can’t ignore it.
1. You can be drawn in
2. People in your business use it
3. The law says so
This is the first in a series of presentations that looks at why you're already in social and gives you a list of important questions to ensure you, your Board and executives know how to answer.
Keynote Slides: Profiting From Technology TrendsRoss Dawson
Slides for Ross Dawson's keynote at National Association of Federal Credit Unions Board of Directors Conference in Maui. Slides were designed to support the keynote, not to be viewed alone. For more see www.rossdawson.com
Centralize OR Decentralize?! Eliminate Decision Failure & See The Future…
From Data to Analytics and Decision Making, new practices to help you succeed today and tomorrow.
One Person's Link Bait is Another Person's News: Understanding Generational C...Michael Leis
Between boomers, Generation X, Millennials, and Generation Z, there are lots of accusations thrown around. But here I take a look at how distinctly each generation approaches technology. I start with understanding the technology people had when they were 14, and apply that through quantitative and qualitative data to unlock trends that help us empathize with the unique qualities of why these generation understand systems and technology so differently.
Dreamforce 2015 - Hack the Tech WorkforceMary Scotton
It's been over a year since Silicon Valley tech companies published their dismal diversity stats, showing the low number of under-represented minorities and women in tech. In response, we've seen a growing community of entrepreneurs and programmers hacking the tech workforce, one hackathon/conference/company at a time. Join us to hear their stories and learn how to implement these hacks in your workplace.
Recording: https://www.salesforce.com/video/192778/
Strata Conference NY: The Accidental Chief Privacy OfficerJim Adler
Strata Conference
New York
September 23, 2011
http://strataconf.com/stratany2011/public/schedule/detail/21484
http://youtu.be/PKUI9iz0l9g
The first generation of chief privacy officers were typically attorneys, charged with the formulation and enforcement of privacy policies. Times have changed. Given the speed and complexity of technology, the privacy policy is necessary but hardly sufficient. Because we live much of our lives in public, both online and offline, the Internet is transforming the anonymity of our cities into the familiarity of small towns. Privacy is deeply ingrained within the technology that manages this personal data. The products and services driving this transformation must consider privacy from the earliest design sessions.
Today’s engineer CPO, and I’m one, must deeply involve themselves with the technology and product design process to bake-in privacy. This new breed of CPO is comfortable in an engineering scrum, product focus group, reviewing pending regulations, or analyzing A/B test results. They have the historical awareness, frontier spirit, regulatory caution, technical chops, and innovator’s curiosity to work through the toughest data issues. The promise of the engineer CPO is that products, not only safeguard privacy, but compete on it.
Speaker Slides: Bringing Agile Management to International DevelopmentMorgan Johnson
Speaker slides from the workshop Bringing Agile Management to International Development hosted by OnFrontiers in Washington DC, July 16, 2019 at the Eaton Hotel.
O'Reilly TOC: A Social Approach to PublishingOpenMatters
Presented at O'Reilly Tools of Change Conference as Key note presentation to publishers to help them better understand the value of social media as part of their e-initiatives.
Machine Learning and/or AI is being adopted across many industries at a rapid pace. But Bias in AI, lack of talent diversity in AI and lack of access to knowledge pose major risks. In this presentation, I showcase some real-life example of Bias in AI. But if we take the right steps we can build an Inclusive AI. Building an Inclusive AI is the right thing to do for the society, it also makes for a great product and business.
This talk is divided in 3 parts: inspiration to study; the business aspects of Artificial Intelligence; and its technical aspects, with a practical demo and technical explanations about Overfitting, NN, CNN, PCA and feature extraction. The code used during the demo will soon be on Github.
Talk on Algorithmic Bias given at York University (Canada) on March 11, 2019. This is a shorter version of an interactive workshop presented at University of Minnesota, Duluth in Feb 2019.
A presentation for public sector professionals about the benefits and risks of social media. Explains how rapid growth in technology is impacting on communication with citizens. Outlines a six-point plan for digital engagement. Gives winning tactics to mitigate risk and protect reputation/
Inclusive tech, (how) is that possible?Marion Mulder
Volgens The Institute For the Future gaan we een tijdperk tegemoet van Human-Machine Partnership, een tijd waar in mens en AI steeds meer gaan samenwerken. Ook zien ze, naast traditionele organisaties, een alternatief opkomen waarin we in communities gaan werken powered by algoritmes.
AI maar ook VR/AR gaan dus een steeds belangrijkere rol spelen. Daarom ben ik mij actief aan het oriënteren op o.a. AI ethics en GenderFreeTech en ben ik actief lid van Women In Voice en Women in AI met als doel een beter beeld te krijgen hoe we kunnen zorgen dat de technologie de we nu creëren en onze toekomst mede bepaalden een wereld creëren die inclusief en goed is voor iedereen. Ik neem jullie vandaag mee in mijn journey en learnings.
Marion Mulder
From Hype to Impact: Applying This Year's SXSW Highlights to Business Transfo...Publicis Sapient
Three of our global thought leaders explore the most coveted topics at SXSW, practical applications to our clients’ business (and our own), and how SapientRazorfish takes these highlights from hype to reality.
Whether you were in Austin or not, top trends are not difficult to find. Which is why we’re taking it a step further. Not only have we shared our takeaways from this year’s sessions, but we've also examined how the conversations at SXSW relate to business reimagined for a connected world.
APD along with partners IBM and Australia Post, hosted ‘Best of the Next’, an event which brought industry leaders and clients together to discuss innovation in the face of digital disruption, and what businesses can do to capitalise on these trends.
The topics discussed by APD’s own Chief Transformation Officer, Inês Almeida and CEO, Scott Player included:
• Artificial Intelligence: Hopes and Fears in Perspective
• The Impact of 5G and Greater Connectivity
• Privacy and security after the Facebook uproar: self-sovereign ID, advertising and Blockchain
Guest speakers Tung Nguyen and Cameron Gough from Australia Post presented their latest innovation around Digital ID.
For more information visit: http://www.apdgroup.com/bestofthenext/
My plenary talk to the California Workforce Association Conference in Monterey, CA, on September 5, 2018. I talked about the role of technology to augment people rather than replace them from my book WTF? What's the Future and Why It's Up to Us, and my ideas about AI and distributional economics, in the context of today's education and workforce development systems. I also summarize some of the work Code for America has been doing on the current state of the California Workforce Development ecosystem.
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62
September 25, 2017
“It’s about what you
do to communicate
to people why
these things are
important. It’s not
about a tweet”
Megan Murphy: Artificial intelligence. People may not know that IBM
doesn’t call it AI. They call it “cognitive computing.” Tell us why that is.
Ginni Rometty: I have actually had to explain this to my husband
as well, because he said to me, “Ginni, of all words, why cognitive?” It
was really a very thoughtful decision. The world calls it AI. There’s so
much fearmongering about AI. When we started over a decade ago,
the idea was to help you and I make better decisions amid cognitive
overload. That’s what has always led us to cognitive. If I considered the
initials AI, I would have preferred augmented intelligence. It’s the idea
that each of us are going to need help on all important decisions. I’m
always reminded of an interesting statistic: When you’re asked what
percentage of your decisions are right, what percentage would you get?
What would it be?
A study said on average that a third of your decisions are really
great decisions, a third are not optimal, and a third are just wrong.
We’ve estimated the market is $2 billion for tools to make better deci-
sions. That’s what led us all to really calling it cognitive and getting
The leader of America’s oldest tech
company talks to Bloomberg Businessweek
Editor Megan Murphy about the
promise and threat of AI (and Watson),
Charlottesville, and being a role model
Ginni
Rometty
CEO, IBM
Photograph
by Stephanie
Sinclair
through to people that, “Look, we really think this
is about man and machine, not man vs. machine.
This is an era—really, an era that will play out for
decades in front of us.”
The world discovered IBM’s Watson after the
computer system beat human competitors and
won $1 million on Jeopardy! It’s named after your
company’s first CEO. What does Watson mean for
the future of AI—and for your business?
Everything you know until today is program-
mable—an entire era for decades has been pro-
grammable. Watson would be the beginning of
a new era where you didn’t program. Machines
would look at data, understand, reason over it,
and they continue to learn: understand, reason
and learn, not program, in my simple definition.
That to us is a very big difference between what
◼ DEBRIEF
63
Bloomberg Businessweek Month 00, 2017Bloomberg Businessweek Month 00, 2017Bloomberg Businessweek Month 00, 2017
6464
you might experience in what I call consumer AI—that is,
general purpose—vs. business. We set out to build an AI plat-
form for business.
There would be two big differences between business and
consum.
Agile Analytics: Delivering on Promises by Atif Abdul RahmanAgile ME
Big Data is all the hype in town yet the real value still remain with delivering analytics that create business impact. Agile Analytics sets out to unleash the true promise usually lost in lengthy, elephantine projects and years of data management purists' pursuits of perfection. That is exactly what separates these big data technologies: They promise greater agility. But is a supportive technology enough or even mandatory to become more agile? We will go through the value chain of delivering high impact analytics using agile practices and devise a jumpstarter kit for you to adopt and adapt.
Transformation, H2O Open Dallas 2016, Keynote by Sri Ambati, Sri Ambati
Transformation with Data and AI, H2O Open Dallas 2016, Keynote by Sri Ambati, founder @h2o.ai @srisatish
- Powered by the open source machine learning software H2O.ai. Contributors welcome at: https://github.com/h2oai
- To view videos on H2O open source machine learning software, go to: https://www.youtube.com/user/0xdata
THE SOCIAL IMPACTS OF AI AND HOW TO MITIGATE ITS HARMSTekRevol LLC
In the wake of mass automation, UBIs might be the answer low-income families and citizens might be looking towards. As automation across industries increases, the induced fear within citizens of its impact is severe. From privacy concerns through rogue AI to doomsday scenarios to more realistic concerns of misused AI and loss of jobs, pop-culture led paranoia has shaken up the world. These concerns have to be dealt with, and tech companies and businesses need to have a robust moral framework under which decisions are made, to ensure any negative externalities of implementing AI are mitigated to the maximum degree. Artificial Intelligence is a great tool to optimize businesses and make our world more efficient, but the moral imperative on all of us is to ensure it happens sides by side human sustainability, not at its expense.
3 Steps To Tackle The Problem Of Bias In Artificial IntelligenceBernard Marr
Artificial intelligence (AI) is facing a problem: Bias. As more and more decisions are being made by AIs, this is an issue that is important to us all. In this article we look at some key steps you can take to ensure AIs of the future are not biased against, e.g., race, gender, sexuality, etc.
A Glimpse Into the Future of Data Science - What's Next for AI, Big Data & Ma...Pangea.ai
We are living in the era of "the fourth industrial revolution". How did we get here? Read this presentation to explore current application trends in Artificial Intelligence (AI,) The Internet of Things (IoT), Big Data, and Machine Learning (ML) technology. Also, to discover the future implications of big data in our lives.
Read the original article here: https://www.pangea.ai/data-science-resources/future-of-data-science/
Work with a data science expert at Pangea: https://www.pangea.ai/
Similar to 2019 WIA - The Importance of Ethics in Data Science (20)
Explore our comprehensive data analysis project presentation on predicting product ad campaign performance. Learn how data-driven insights can optimize your marketing strategies and enhance campaign effectiveness. Perfect for professionals and students looking to understand the power of data analysis in advertising. for more details visit: https://bostoninstituteofanalytics.org/data-science-and-artificial-intelligence/
Data Centers - Striving Within A Narrow Range - Research Report - MCG - May 2...pchutichetpong
M Capital Group (“MCG”) expects to see demand and the changing evolution of supply, facilitated through institutional investment rotation out of offices and into work from home (“WFH”), while the ever-expanding need for data storage as global internet usage expands, with experts predicting 5.3 billion users by 2023. These market factors will be underpinned by technological changes, such as progressing cloud services and edge sites, allowing the industry to see strong expected annual growth of 13% over the next 4 years.
Whilst competitive headwinds remain, represented through the recent second bankruptcy filing of Sungard, which blames “COVID-19 and other macroeconomic trends including delayed customer spending decisions, insourcing and reductions in IT spending, energy inflation and reduction in demand for certain services”, the industry has seen key adjustments, where MCG believes that engineering cost management and technological innovation will be paramount to success.
MCG reports that the more favorable market conditions expected over the next few years, helped by the winding down of pandemic restrictions and a hybrid working environment will be driving market momentum forward. The continuous injection of capital by alternative investment firms, as well as the growing infrastructural investment from cloud service providers and social media companies, whose revenues are expected to grow over 3.6x larger by value in 2026, will likely help propel center provision and innovation. These factors paint a promising picture for the industry players that offset rising input costs and adapt to new technologies.
According to M Capital Group: “Specifically, the long-term cost-saving opportunities available from the rise of remote managing will likely aid value growth for the industry. Through margin optimization and further availability of capital for reinvestment, strong players will maintain their competitive foothold, while weaker players exit the market to balance supply and demand.”
Chatty Kathy - UNC Bootcamp Final Project Presentation - Final Version - 5.23...John Andrews
SlideShare Description for "Chatty Kathy - UNC Bootcamp Final Project Presentation"
Title: Chatty Kathy: Enhancing Physical Activity Among Older Adults
Description:
Discover how Chatty Kathy, an innovative project developed at the UNC Bootcamp, aims to tackle the challenge of low physical activity among older adults. Our AI-driven solution uses peer interaction to boost and sustain exercise levels, significantly improving health outcomes. This presentation covers our problem statement, the rationale behind Chatty Kathy, synthetic data and persona creation, model performance metrics, a visual demonstration of the project, and potential future developments. Join us for an insightful Q&A session to explore the potential of this groundbreaking project.
Project Team: Jay Requarth, Jana Avery, John Andrews, Dr. Dick Davis II, Nee Buntoum, Nam Yeongjin & Mat Nicholas
Levelwise PageRank with Loop-Based Dead End Handling Strategy : SHORT REPORT ...Subhajit Sahu
Abstract — Levelwise PageRank is an alternative method of PageRank computation which decomposes the input graph into a directed acyclic block-graph of strongly connected components, and processes them in topological order, one level at a time. This enables calculation for ranks in a distributed fashion without per-iteration communication, unlike the standard method where all vertices are processed in each iteration. It however comes with a precondition of the absence of dead ends in the input graph. Here, the native non-distributed performance of Levelwise PageRank was compared against Monolithic PageRank on a CPU as well as a GPU. To ensure a fair comparison, Monolithic PageRank was also performed on a graph where vertices were split by components. Results indicate that Levelwise PageRank is about as fast as Monolithic PageRank on the CPU, but quite a bit slower on the GPU. Slowdown on the GPU is likely caused by a large submission of small workloads, and expected to be non-issue when the computation is performed on massive graphs.
2. Jennifer Prendki, PhD
Founder and CEO, Alectio
More about me:
• Currently Expert Network @ IIA
• Previously VP of Machine Learning @ Figure Eight,
Chief Data Scientist @ Atlassian
• Managed Applied Data Science Research in the Search team
@ Walmart Labs
• Have built & scaled ML functions in companies of all sizes
3. ALECTIO’S MISSION:
Sustainable Machine Learning
Helping Machine Learning teams build Machine
Learning models with less resources (starting with
less data)
4. AGENDA
• Data: The New Oil?
• Fatally Unprepared?
• Data At All Costs?
• Insane(ly Good) Machine Learning
• Responsible Data Science
ETHICS IN DATA SCIENCE AND MACHINE LEARNING
5. Data: The New Oil?
WHY WE DATA SCIENTISTS LOVE OUR DATA…
21. Progress… or Global Societal Abuse?
Disappearance of Privacy
Abuses of the Data
Economy
$
22. Progress… or Global Societal Abuse?
Disappearance of Privacy Automation of Unfairness
Abuses of the Data
Economy
$
23. Progress… or Global Societal Abuse?
Disappearance of Privacy Automation of Unfairness
Abuses of the Data
Economy
Malevolent Applications
$
24. Data At All Costs?
THE IMPACT OF THE BIG DATA ECONOMY ON SOCIETY
25. Datafication:
a modern technological trend turning
many aspects of our lives into data which
is subsequently transferred into
information realized as a new form of
value.
27. A Brief History of Data Privacy
Google
Street View
Behavior
targeting
is targeted
Facebook Apps
harvesting data
w/out consent
Voicemail
Hacking
Facebook &
Cambridge Analytica
GDPR
EU Treaty went
into effect
Creation of the
European Data
Protection Directive
Privacy in the
News
Proposal of
GDPR Released
Adoption by the
EU Parliament
GDPR valid
29. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
30. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
31. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
32. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
33. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
34. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
35. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
Slow human <> job matching
Overall
36. Data Labeling and the Gig Economy
The human side of A.I.
o A dependency on human labor
Good side: communities
o A challenge for the workers
A tougher job than it might seem…
Slow human <> job matching
Overall
o Inconsistent qualify of work
Error-prone tasks
Subjective tasks
40. Biases All Over the Place…
DATA BIAS
o Labeling Bias
Subjective Labeling Tasks
o Subgroup Validity
Simpson’s Paradox
o Representation
Inappropriate Sampling Strategy
41. Biases All Over the Place…
DATA BIAS ALGORITHMIC
BIAS
o Labeling Bias
Subjective Labeling Tasks
o Subgroup Validity
Simpson’s Paradox
o Representation
Inappropriate Sampling Strategy
o Involuntary
Statistical Stereotyping
o Voluntary
Agenda-Based
50. A Fairer AI Economy
o General Patterns > Granular Insights
51. A Fairer AI Economy
o General Patterns > Granular Insights
o Social Impact > Feasibility
52. A Fairer AI Economy
o General Patterns > Granular Insights
o Social Impact > Feasibility
o Human + Machine Collaboration > Competition
53. A Fairer AI Economy
o General Patterns > Granular Insights
o Social Impact > Feasibility
o Human + Machine Collaboration > Competition
o Ethics by Design > Legislation
54. Fairness vs. Biases
• With ML, biases are of the essence… and that’s a good thing!
• (Yes, you read that right!)
55. Fairness vs. Biases
• With ML, biases are of the essence… and that’s a good thing!
• (Yes, you read that right!)
• Fairness is not ingrained in Machine Learning
• Machines learn what we humans teach them
• (Yes, even in the case of Reinforcement Learning)
56. Fairness vs. Biases
• With ML, biases are of the essence… and that’s a good thing!
• (Yes, you read that right!)
• Fairness is not ingrained in Machine Learning
• Machines learn what we humans teach them
• (Yes, even in the case of Reinforcement Learning)
Unfairness ≠ Bias
ML is born of biases, but its societal purpose dies with unfairness
57. Responsible A.I.
o Ethical
o Inclusive (not exclusive to a privileged group)
o No harm to society (no weaponization)
o Centered on the well-being of Society
58. Be the Change you
want to see in the World
o Machine Learning will not become fair on its
own
ML algorithms are by-products of human-generated
data
o Society and politicians are not ready
Uneducated users
No appropriate legislation in place
o The one true prevention of unethical use of
data is the Data Community
CongresshearingofMarkZuckerberginApril
2018