How good are you working with intelligent machines?
“Are you good at working with intelligent machines or not? Are your skills a complement to the skills of the computer, or is the computer doing be;er without you?”
Overview
Social DisrupAon -‐ Some data/research • how work gets done within companies • loss of jobs/acAviAes and changing nature of work • augmented rather than fully replaced
Systems Thinking and IntenAonal Networks – ExplanaAon and Examples • enhanced decision making • become informed and engaged in use or understanding of network analysis at scale (individual, group/project, organizaAonal) as automaAon transforms work.
Ethics • social research without our knowledge
ExponenAal Rate Change
Oxford University report 2011 and McKinsey research
Key findings Oxford:
• 47% of all US jobs were at risk from automaAon
Key findings McKinsey:
• Less than 5% of of jobs can be fully automated
• Below the job or occupaAon level to work acAviAes 45% of work is automatable by current technologies. Included were high wage, high skilled jobs.
h;p://bits.blogs.nyAmes.com/2015/11/06/automaAon-‐will-‐change-‐jobs-‐more-‐than-‐kill-‐them/?_r=0
… while sophisAcated algorithms and developments in Mobile RoboAcs (MR), building upon with big data, now allow many non-‐rouAne tasks to be auto-‐mated, occupaAons that involve complex percepAon and manipulaAon tasks, creaAve intelligence tasks, and social intelligence tasks are unlikely to be subsAtuted by computer capital over the next decade or two. The probability of an occupaAon being automated can thus be described as a funcAon of these task characterisAcs …
h;p://www.oxfordmarAn.ox.ac.uk/downloads/academic/The_Future_of_Employment.pdf
More specifically, our research suggests that as many as 45 percent of the acAviAes individuals are paid to perform can be automated by adapAng currently demonstrated technologies.4 In the United States, these acAviAes represent about $2 trillion in annual wages. Although we oeen think of automaAon primarily affecAng low-‐skill, low-‐wage roles, we discovered that even the highest-‐paid occupaAons in the economy, such as financial managers, physicians, and senior execuAves, including CEOs, have a significant amount of acAvity that can be automated.
The Four Fundamentals:
1. AutomaAon of acAviAes 2. RedefiniAon of jobs and
business acAviAes 3. Impact on high-‐wage
occupaAons 4. Future of creaAvity – 4% and meaning – 29% (emoAon)
ConnecAons below the surface are where tacit informaAon is mined, machine learning begins and is applied via algorithms at massive scale.
h;ps://research.facebook.com/
Everything we do at Facebook is seen as a graph. (2012)
Cameron Marlow Former Head and Founder, Data Science Facebook
h;p://www.scienAficamerican.com/arAcle.cfm?id=social-‐scienAsts-‐might-‐gain-‐access-‐facebooks-‐data-‐use
Predict 2 week market adopAon lead Ame!
TradiAonal Network Science
Friend Paradox
TED -‐ Christakis
It may not qualify as a lightning-‐bolt eureka moment, but Jeffrey R. Immelt, chief execuAve of General Electric, recalls the June day in 2009 that got him thinking. He was speaking with G.E. scienAsts about new jet engines they were building, laden with sensors to generate a trove of data from every flight — but to what end?
That data could someday be as valuable as the machinery itself, if not more so. But G.E. couldn’t make use of it.
“We had to be more capable in soeware,” Mr. Immelt said he decided. Maybe G.E. — a maker of power turbines, jet engines, locomoAves and medical-‐imaging equipment — needed to think of its compeAtors as Amazon and IBM.
Predix Soeware When he lee Apple, Mr. Haas was head of cloud engineering, managing the compuAng engine behind Siri, iTunes and iCloud. At GE Digital, Mr. Haas has a similar Atle, head of plasorm cloud engineering, but in a different setng. He describes his job as applying modern soeware technology — machine learning, arAficial intelligence and cloud compuAng — to the industrial arena. “I’ve got my work cut out for me,” he said.
GE Backstory OrganizaAonal Business Case Individual who automates
work
biochemicaldiagnostics
onlinerecruiting
music
fi nancial
payments
e-commerce
networks securitysecurity
cloud storagecloud storage
dataanalytics
telecom
health carehealth careIT
semiconductors
biologicsbiologics
search
biofuels
education
wind
solar
smart grid
travelreal estate
geolocation
imaging
medical devices
batteries
lighting LEDs
Locating Your Next Strategic Opportunity
To map semantic clus-ters, Quid software fi rst identifi es hundreds of key phrases associated with individual companies and organizations, or their
“n-grams.” Applying algo-rithms and other analyti-cal tools, the technology parses text in millions of corporate documents, from patent fi lings, to press releases, to Twitter posts. The software then creates a map with lines connecting companies whose n-grams are alike.
The lines act like gravita-tional pull: The more lines there are between com-panies, the more tightly together those companies are drawn. Similar fi rms become clustered into industry sectors.
The result is a multi-dimensional industry map like the one below. It represents 4,000 tech-nology enterprises—from venture-backed start-ups to established public companies—that received media coverage and
Where and how do strategists fi nd growth opportunities? Sometimes by literally drawing a map, using a technique called semantic-clustering analysis. Such maps can reveal not only which sectors are thick with competition but where in the market white spaces are open for the taking. For example, while it may seem odd to fi nd opportunity in the nexus between gaming and biopharma, seeing is believing.Data and visualization by Sean Gourley of Quid; graphic design by Open
gaming social media
genomicsbiopharma
ad targeting
IDEA WATCH
34 Harvard Business Review March 2011
Vision Statement
Semantic-clustering software locates and analyzes the documents in a company’s digital footprint.
Documents are catego-rized and weighted for importance.
The software then identifi es the company’s n-grams, or key phrases.
The company’s n-grams are then compared with other companies’ n-grams.
The process is then repeated for every company in the sample to generate the map.
When at least 80% of their n-grams are similar, companies are linked on the map.
How N-Gram Mapping Works
showed capital growth last year .
Such maps expose surprising relationships between and across sectors and, even more tantalizing, the white spaces among them—which can o! er fi rms strategic opportunities to connect companies operat-ing in di! erent markets, to take existing products into new sectors, or to innovate with products and services no one has even dreamed up yet."
HBR Reprint F##$%Z
The Pharma-Gaming Connection One of the most intriguing white spaces on this map is surrounded by some industry sectors that at fi rst glance may seem unlikely to be connected: biopharma, gaming, social media, and ad targeting. As shown in the box below, Selventa, Proximic, Vivo, Insilicos, Foldit, and Nvidia are some of the ventures seizing the strategic opportunities in this space.
Sean Gourley is CTO and cofounder
of Quid, in San Francisco. Open is a design studio in New York.
Nvidia
Foldit
Vivo Selventa
InsilicosProximic
gaming social media
genomicsbiopharma
ad targeting
Profi ling and Per-sonalized Medicine Selventa makes targeted drug discoveries by analyzing large amounts of patient data and statistically identify-ing patient cohorts that will respond well to special-ized treatments. To do so it borrows mathematical techniques from ad targeting companies like Proximic.
Gaming Meets Drug Discovery Nvidia builds graphics pro-cessing units used in video games, among other things. Recognizing that work done by biomarker discovery and diagnostic development companies like Insilicosrequires similarly intense graphics processing, Nvidia has edged into the drug discovery space.
Solving Business Problems SociallyFoldit is an online social game for science geeks based on the challenge of fi nding the most e& cient way to fold proteins. But the thousands who play it can help solve real protein- folding challenges for bio pharma companies, which have begun putting the gaming platform to work.
Scientifi c Social NetworkingVivo jumped into the white space between social gaming and pharma by building a Facebook-like online collabo-ration platform that helps scientists connect and share research and data.
March 2011 Harvard Business Review 35
HBR.ORG
We believe that the same AI technology that gives big tech companies a compeAAve edge should be available to developers or businesses of any size or budget. That’s why we built our new Custom Training and Visual Search products – to make it easy, quick, and inexpensive for developers and businesses to innovate with AI, go to market faster, and build be;er user experiences.
Sales to physicians confirmed at 95% rate using Nugget
Ethics – Who is minding the transforma<on on the Future of Work?
Thank You!
Victoria G. Axelrod Principal, Axelrod Becker ConsulAng 445 East 86th Street New York, NY 10028 212-‐369-‐2885 [email protected] www.axelrodbecker.com Blog: 21st Century OrganizaAon h;p://c21org.typepad.com
What’s your comfort level working with intelligent machines?
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