artificial intelligence · humans and artificial intelligence. five principles can help them do so:...

ARTIFICIAL INTELLIGENCE

THE INSIGHTS YOU NEED FROM HARVARD

BUSINESS REVIEW

BY HARVARD BUSINESS REVIEW,

THOMAS H. DAVENPORT, ERIK

BRYNJOLFSSON, ANDREW MCAFEE,

AND H. JAMES WILSON

Contents

Figure 1-1 3

Table 1-1 4

Figure 2-1 5

Figure 2-2 6

Figure 2-3 7

The Value of Collaboration 8

Table 9-1 10

Vision error rate30%

25

20

15

10

Humans

Algorithms

5

02010 2011 2012 2013 2014 2015 2016

F I G U R E 1 - 1

Machines have made real strides in distinguishing among similar- looking categories of images

Source: Electronic Frontier Foundation

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3

T A B L E 1 - 1

Supervised learning systemsAs two pioneers in the field, Tom Mitchell and Michael I. Jordan, have noted, most of the recent pro gress in machine learning involves mapping from a set of inputs to a set of outputs. Some examples:

Input X Output Y ApplicationVoice recording Transcript Speech recognition

Historical market data Future market data Trading bots

Photo graph Caption Image tagging

Drug chemical properties Treatment efficacy Pharma R&D

Store transaction details Is the transaction fraudulent?

Fraud detection

Recipe ingredients Customer reviews Food recommendations

Purchase histories Future purchase be hav ior Customer retention

Car locations and speed Traffic flow Traffic lights

Faces Names Face recognition

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4

H3R&D AML

Prod

uct r

eadi

ness

Time

Product deliveryH2 H1

F I G U R E 2 - 1

Where AI fits in at Facebook

Source: Facebook

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5

Translation

Naturallanguage

Speech

Camera

Computervision

Computerphotography

Visual

Audio

Text

F I G U R E 2 - 2

Applied machine learning

Source: Facebook

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6

AI/ML expertise required

Ease of use

Ability to build and customize AI

Self-serve AIFor non-technical users, e.g. Lumos

Reusable enginesFor developers outside of AML, e.g. CLUE

ML algorithmsGeneralizable by discipline

Deep learning frameworkCaffe2

AI backboneFBLearner Flow











Less

More

Less

More

Less

More

F I G U R E 2 - 3

Layer cake of AI

Source: Facebook

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7

The Value of CollaborationCompanies benefit from optimizing collaboration between

humans and artificial intelligence. Five princi ples can help

them do so: Reimagine business pro cesses; embrace ex-

perimentation/employee involvement; actively direct AI

strategy; responsibly collect data; and redesign work to

incorporate AI and cultivate related employee skills. A sur-

vey of 1,075 companies in 12 industries found that the more

of these princi ples companies adopted, the better their AI

initiatives performed in terms of speed, cost savings, rev-

enues, or other operational mea sures (see the figure).

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8

7x

6x

5x

4x

3x

2x

1x

0xPerf

orm

ance

impr

ovem

ent

Number of human-machine collaborationprinciples adopted(O indicates the adoption of only basic,noncollaborative AI)

0 1 2 3 4 5

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9

T A B L E 9 - 1

Enhancing per for manceAt organ izations in all kinds of industries, humans and AI are collabo-rating to improve five ele ments of business pro cesses.

Ele mentBusiness pro cess

Com pany or organ ization Type of collaboration

Flexibility Auto manufacturing

Mercedes- Benz Assembly robots work safely alongside humans to customize cars in real time.

Product design Autodesk Software suggests new product design concepts as a designer changes par ameters such as materials, cost, and per for mance requirements.

Software development

Gigster AI helps analyze any type of software proj ect, no matter the size or complexity, enabling humans to quickly estimate the work required, or ga nize experts, and adapt workflows in real time.

Speed Fraud detection

HSBC AI screens credit- and debit- card transactions to instantly approve legitimate ones while flagging ques-tionable ones for humans to evaluate.

Cancer treatment

Roche AI aggregates patient data from disparate IT systems, speeding collaboration among specialists.

Public safety Singapore government

Video analytics during public events predicts crowd be-hav ior, helping responders address security incidents rapidly.

Scale Recruiting Unilever Automated applicant screening dramatically expands the pool of quali-fied candidates for hiring man ag ers to evaluate.

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10

Ele mentBusiness pro cess

Com pany or organ ization Type of collaboration

Scale (conti nued)

Customer ser vice

Virgin Trains Bot responds to basic cus-tomer requests, doubling the volume handled and freeing humans to address more- complex issues.

Casino management

GGH Morowitz Computer- vision system helps humans continuously monitor every gaming table in a casino.

Decision making

Equipment maintenance

General Electric

“Digital twins” and Predix diagnostic application pro-vide techs with tailored rec-ommendations for machine maintenance.

Financial ser vices

Morgan Stanley Robo- advisers offer clients a range of investment options based on real- time market information.

Disease prediction

Icahn School of Medicine at Mount Sinai

Deep Patient system helps doctors predict patients’ risk of specific disease, allowing preventive intervention.

Personal-ization

Guest experience

Carnival Corporation

Wearable AI device streamlines the logistics of cruise- ship activities and an-ticipates guest preferences, facilitating tailored staff support.

Health care Pfizer Wearable sensors for Par-kinson’s patients track symptoms 24/7, allowing customized treatment.

Retail fashion Stitch Fix AI analyzes customer data to advise human stylists, who give customers individualized clothing and styling recommendations.

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