Artificial Intelligence for Happiness of People

© Hitachi, Ltd. 2017. All rights reserved.

Kazuo Yano

Artificial Intelligence for Happiness of People

PhD, IEEE Fellow

Corporate Chief Scientist

R & D Group, Hitachi, Ltd.

Changes We Face Now

Demand

21st Century20th Century

Supply

Profit

from

Result

Common infrastructure

for life & society

Diversified & short-

term needs

Mass production

at factory

Customization for complex

& unforeseen change

Repeated standardized

work for scaling

Automatic customization &

adaptation for scaling (by AI)

1st productivity revolution

Larger middle layer &

environmental load

2© Hitachi, Ltd. 2017. All rights reserved.

2nd productivity revolution

Recovery of middle-layer &

environment

What We Really Need is

To Face Changing, Diversified

& Unforeseen Futures



From Rule-Oriented

To Outcome-Oriented


Conventional

Rule-Oriented System

Computer

Program

Code

Business & Society

Input Output

Instruction Hypothesis

Rigid

Business & Society

Input Output

・Sensor

・Camera

・Robot

・Wearable

Big Data

Automatic

Learning from Facts

Emerging

Outcome-Oriented System

Artificial

IntelligenceFlexible

5


・Issue 1 Start from Upper Business Objective (Outcome)

・Issue 2 Requires Limited Data

・Issue 3 Embrace the Existing Systems

Business Requires


System

Existing

System

IT &Facility

Outcome-Oriented System

H

ＡＩ

Hitachi AITechnology

Monitoring

Control

7

Learns from data, adaptively grows,

and gets the results

◆1 Outcome & in/out defined by

humans

◆2 Without inputs of domain

knowledge nor logic

◆3 Added-on to existing system

Demonstration

動画デモ２

鉄棒

Learning the Intelligence from Life

Alan Turing(1912-1954)

John von Neumann(1903-1957)

"Computing Machinery and Intelligence"(1950)

"The General and Logical Theory of Automata"(1948)

© Hitachi, Ltd. 2017. All rights reserved. 12

13

A

T

G

C

ＤＮＡ


14

Genetic Evolution

BoldNeural Brain

Cautious X

Leap Learning

Input

Table

Function

Automatic Discovery of Unexpected Factors

(Patent Granted JP6067882 JP6082564)

Compound Factors

Seed・Merchandize・Shelf・Employee

Extract Important Factors

Compound

Factors

Generation

Weight

Variables

1k～1M 3～1000Seed 10～100

Input Output

15


Best of Both Worlds

Genetic Evolution Neural Brain

16

Warehouse

Checking & Packing Picking



System

Existing

WMS

AI-Based Warehouse Management System

A I

Hitachi AITechnology/

H

Monitoring

Control

18


and provides the results

◆1 Outcome is defined as “total

work time”

◆2 No inputs of warehouse

knowledge nor logic

◆3 Added-on to existing WMS

system

WMS = Warehouse Management System


Artificial Intelligence Helps Workers

Optimize Work Orders

Workers Help Artificial Intelligence Input

a Variety of Data that Affect Outcome

8am 1am

AI-Based Warehouse Management SystemWorking & Learning Daily Added on Existing WMS

with 8% Productivity Enhancement

20


System

Existing

ID-POS

AI-Based Store Management System

A I


H

Monitoring

Control

21



◆1 Outcome is defined as

“sales per customer”

◆2 No inputs of store knowledge

nor logic

◆3 Added-on to existing POS

system

POS = Point of Sales

Human vs. AIRule: Increase customer sales based on 10-day data

Artificial IntelligenceRetail Specialists (2 persons)

ApproachInterviews with executive etc

Use of domain knowledge

Data only

No domain knowledge

ActionPOP ads for focus items &

item rearrangement

Employee presence at

hot spot Identified

Result No sales increase confirmed Sales per customer was

increased by 15%

Computer with big data enhances business performance



Hot-Spot Employee Presence Enhanced Sales

100% 115%

24

Railway


System A I

Monitoring

Control

Existing

Railway

Monitoring

System

ＡＩ-Based Railway Monitoring System


Ｈ




◆1 Outcome is defined as

“Reducing Electricity”

◆2 No inputs of railway

knowledge nor logic

◆3 Added-on to existing

monitoring system

5 10 15 20 25 30 35 40 45 50050100150200250

5 10 15 20 25 30 35 40 45 500123456789

5 10 15 20 25 30 35 40 45 50050100150200250

5 10 15 20 25 30 35 40 45 500123456789

26

AI Discovers Low-Power Operation

■Electricity

532kWh

■Occupancy30％

■Electricity

654kWh

■OccupancyFull

Operating A

Operating BNotch OFF

Distance

Distance

Sp

eed

Sp

eed

Co

mm

and

（N

otc

h）

Co

mm

and

（N

otc

h）

Optimized Operation Enables 14% Power Saving (Annual Prospect)


PX

High Pressure Pump （High Power）

Pressure Monitor（Outcome） RO unit

for Mixed Water

RO unit

UF unit

Sea Water

Sewage

MixedWater

Desalinated Water

Water Desalination System (Remix Water)

27

Water Plant: Electricity Saving

6% Saving in Electricity Cost


Kabu.com utilizes Hitachi's AI for stock lending.

1000 types of data allow Hitachi's AI for pricing

as good as experts with much higher throughput.

Stock Lending

Kabu.com

News Release

16.7.25


Sumishin SBI Net Bank has started co-creation

with Hitachi for credit scoring for loan.

Credit Scoring for Loan

News Release

16.9.30

30

Fraud-Trade Detection at Tokyo Stock Exchange

News Release 17.2.28


ASKUL Corporation

News Release 16.6.2816.9.30E-Commerce

Just-In-Time Delivery

with Logistics Big Data

Both by Hitachi AI Technology / H

Customized Marketing

with Purchase Big Data

EC Marketing Lab

Multi-Purpose AI

14 Domains

57cases

Hitachi AI Technology/H


33

Multi-Purpose AI has been Developed


Special-Purpose AI Multiple-Purpose AI

Independent Software is

Developed for each Problem

The Same Software is Used for

a Variety of Problems

・Retail Recommend

Order

Delivery

・Finance Recommend

Sales Assignment

Fraud Detection

Employee Engagement

Example

・Retail Recommend

・Ads Web Search

・Telephone Voice Recognition

・Communication Machine Translation

・Medical Q & A

・Car Auto-Drive

Example


1. Outcome (KPI) Quantified

2. AI-assisted Actions Needed

3. Data for Conditions Recorded

Three Conditions

Evolution of AI


Level 1Special-Purpose ＡＩ

Level 2 Multiple-Purpose AI

Learning

DataGathering

Execution

DataStorage

Visualization

Decision

Optimization

Modeling

Application-Specific

DataGathering

Execution

DataStorage

Visualization

SpecialPurpose

Learning

Decision

Optimization

Modelling

GeneralPurpose

Independent


Level 3Creative AI

SpecialPurpose

GeneralPurpose

Actuation(Drug/Software)

CreationDialogScope

Evolution of AI

Learning

DataGathering

Execution

DataStorage

Visualization

Decision

Optimization

Modeling

Independent

Level 4General Intelligence(AGI)

SpecialPurpose

GeneralPurpose

Learning

DataGathering

Execution

DataStorage

Visualization

Decision

Optimization

Modeling

Independent

Actuation(Drug/Software) Creation


Artificial Intelligence

From Rule-Oriented

To Outcome-Oriented

38

Physical Motion Walk

E-Mail

1S

1S

2Hz

0.8HzWristband Sensor


Badge Sensor


0 24

2009

1

2

3

4

5

6

7

8

9

10

11

12

My Life has been Recorded for over 10 Years every 50 ms


My Life has been Recorded for over 10 Years every 50 ms

0 24

2009

1

2

3

4

5

6

7

8

9

10

11

12

Time

0 24 0 24 0 24 0 24

20132010 2011 2012 2014

0 24 0 24

2015 2016

0 24

0 24

41

On

e Y

ea

r

ＡＢＣＤ

0 24Hour 0 24Hour 0 24Hour 0 24Hour

"Life Tapestry(R)" of Four Persons


42© Hitachi, Ltd. 2017. All rights reserv ed.

1,000,000 DaysCollected Human-Behavior Data Last 10 Years

Hap

pin

ess

Su

rvey

Diversity of Physical Motion

R=0.94


5 billion records: 10 organizations, 468 persons, 5000 man-days

Diversity of Physical Motion is Happiness

Happiness Questionnaire

20 questions on last week's

happiness, enjoyment,

solitude, sadness, etc.


Active

Non-Active

Large

Small

Diversity

of Motion Short Long

Time

MediumMedium

Hidden Pattern behind Happy PeopleDiversity in Motion Length (= Vitalization)


Happiness of People is Measurable by Accelerometer


Productive

Happy Organization is


34%

Sale

s Per Hour

Collective Happiness

＝ Diversity of Motion

(Daily Average)

Low High0

0.5

0.8

Call Center Store

15%

Sale

s per

Cus

tom

er （¥

）

Low High

Development Project

17141312

5 Y

ear

Reve

nue

0

4

8

12

PJ1 PJ2

PJ3

PJ4



(Daily Average)



(First 2 Month)


Human

Empower Human

A I


Ｈ

Monitor

Assist

48

Support Organizational

Learning & Growing

◆Outcome is Collective

Happiness

◆Daily Advice by AI for Better

Communications


Quantify Daily Group Happiness by Wearing Sensors

50

Daily activeness & success rate

Priority list

to support

Supervisor comment share

Recent

commentsMeeting Activeness Sales

Dashboard for Supervisor


Sales Success Rate 27%↑

Employee Happiness ↑

Bank of Tokyo Mitsubishi UFJ 15.9.25

AI-Based Big-Data Analytics Assists

Productivity Enhancement in BTMU

Japan Airline 15.10.5JAL & Hitachi has Started Pilot Utilizing IoT &

AI for Employee-Satisfaction Enhancement

Happiness AI Application 53

Activation VisualizationType Diagnosis & Advice

Evidences

Hitachi Utilizes ＡＩFinance, Sales, Manufacturing, HR

600 Sales Employees in Hitachi Group Use AI

（2016.6.27 News Release）



Happiness Measurement by Smart PhoneAttendees for Experiment in January is Welcome

(Search by “Happiness Planet”)

News Release, HitachiOctober 3rd 2017

Artificial Intelligence

releases you from rules,

makes you bloomat the place you are placed
