coming of age of artificial intelligence - irpaai · artificial intelligence toolbox –various...
TRANSCRIPT
Coming of Age of Artificial Intelligence
Disruption, Transformation Ahead
Cyrille Bataller
Copyright © 2015 Accenture All rights reserved. 2
Unified Desktops/Mashups
Robotics in Business Operations: Understanding the Landscape
Robotic Process Automation
Artificial Intelligence
Cognitive Robotics/ Virtual Agents
Multiple screens are consolidated into
a single view for the operator thus
saving the time to toggle between
screens. Suitable for contact center
type applications.
Automation of transactions and work
flow activities by handling input,
processing, and output of data across
systems.
Systems that gain knowledge from
data as “experience” and generalize
what is learned in upcoming situations.
Sense, comprehend, act – and learn.
Natural language dialogue.
Robotics
Spectrum
Basic Automation – Minibots
Applying technology to manipulate
existing application software to
complete a process. Primarily based
on XL, AutoHotKey, or Visual Basic.
Copyright © 2015 Accenture All rights reserved. 3
AI: IT Systems that can Sense, Comprehend, Act – and LearnMaybe the Most Disruptive Emerging Technology on the Horizon
Artificial Intelligence enables machines to interact naturally with their
environment, people and data. These systems create more intuitive interactions
and extend the capabilities of what either human or machine can do on their own.
From coding to training
AI enables intelligent systems that learn from a body of knowledge
without analyzing and coding all business rules manually.
Advances in machine learning, coupled with big
data and cheap, ubiquitous cloud computing
will unleash remarkable new potential for
organizations across industries.
Copyright © 2015 Accenture All rights reserved. 4
AI: IT Systems that can Sense, Comprehend, Act – and LearnA Collection of Technologies Underpinned by Machine Learning
Source: Gartner's Hype Cycle for Human-Computer Interactions
Artificial Intelligence encompasses
multiple technologies that enable
computers to
• perceive the world (e.g.,
computer vision, audio
processing or sensor
processing)
• analyze and understand the
information collected (e.g.,
natural language processing or
knowledge representation)
• make informed decisions
(e.g., inference engines,
machine learning/deep learning
or expert systems)
Copyright © 2015 Accenture All rights reserved. 5
Initial research focused on Artificial Intelligence (AI), "the science aiming to create intelligent machines that are as capable as humans.”
Distinction between “strong” and “weak” AI. Also, recently, the focus has shifted from AI to Intelligence Augmentation (IA), intelligent systems that can support humans in their activities.
Artificial Intelligence HistoryVarious Attempts and “Winters” since Computing was Invented
Source: Accenture
Secondary Research
Audi’s driverless
race car
Border control
“robots”
Google driverless car
1.7M miles accident-free
Ask Sgt Star
Ask Jenn
Copyright © 2015 Accenture All rights reserved. 6
Artificial Intelligence Toolbox – Various Application Domains
Text AnalyticsResearch Assistants
Image AnalyticsMultimedia
SearchCognitive Robotics
Virtual Agents Expert Systems
Video Analytics Identity Analytics Speech Analytics Data VisualizationDomain-specific
CalculationsRecommendation
SystemsSelf-Adjusting IT
Systems
- Text Analytics: process large volumes of unstructured text and classify/group etc
- Research Assistant: natural language search engine to retrieve subset of relevant documents from large unstructured dataset
- Deep Learning: apply deep learning to detect certain characteristics – e.g. cancer tumor in MRI scan, or find tall trees from a drone
- Multimedia Search: retrieve specific images, videos or sounds based on content rather than user metadata
- Cognitive Robotics: automate manual processes using UIs to access multiple systems e.g. testing, claims processing
- Virtual Agent: automate helpdesks to solve user issues
- Expert System: learn a product manual and answer questions or assist a user with step by step instructions
- Video Analytics: apply computer vision to CCTV cameras
- Identity Analytics: recognize people based on what they have/are/know/do incl. biometrics
- Speech Analytics: speech to text/speech recognition, text to speech
- Data Visualization: ask questions in natural language on large structured dataset
- Domain-specific Calculations: perform calculations for a specific domain in natural language
- Recommendation Systems: provide “people like you” type recommendations
- Self-Adjusting IT Systems: ability for IT system to adjust based on historical usage patterns
Sense
Comprehend
Act
Computer Vision
Audio Processing
Sensor ProcessingNatural Language Processing
Knowledge RepresentationInference Engines
Machine Learning
Expert Systems
Technologies
Capabilities
Solutions
Affective Computing
AutomaticTrend
Detection
Anomaly Detection
Semantic Web
Ontology Learning
Augmented Reality
Text Analytics
Copyright © 2015 Accenture All rights reserved. 8
Case Study: PharmacoVigilanceMonitoring Adverse Drug Reactions
Creation of Adverse Drug Events (ADE) is required for assessing safety of a drug against usage, severity
etc. NLP can help generate Adverse Event signals from various therapeutic reports, establish
associations and report suspected new cases
Individual Case Safety
Reports and
Narratives database
Regulatory
warning and self
reporting
Social and
Public Data
Text Screening
and extractionEntity
Recognition
Semantic
modeling and
signal
generation
Case
Suggestion
Relevant text
portions are
extracted
1Entities like
Patient,
Symptom,
Drug, Usage
etc. are
recognized
2Relationships
between
Patients,
Disease,
Symptom,
Drug, Dosage
etc are
established
3Based on
Statistical
association
measures on
aggregate data
a case is
suggested to
the writer
4
Assisted PV Processing
Copyright © 2015 Accenture All rights reserved. 9
Accenture Text Analyzer for PharmacoVigilance
Copyright © 2015 Accenture All rights reserved. 10
Accenture Text Analyzer for PharmacoVigilance
Inference on Expectedness and Causality
Cognitive Robotics
Copyright © 2015 Accenture All rights reserved. 12
Benefits of Robotic Automation
Reduces transactional errors
Drives higher accuracy
Mistake proof processes
Enhances compliance & controls
Drives improvements in business outcome through improvement in time, quality &
cost of transaction
Accelerating business outcomes without increasing program complexity or headcount
Increases customer satisfaction
Reduces cost, as we automate transaction processing
Helps to provide higher productivity benefits
Higher efficiency in process & reduction of non value added activities
Copyright © 2015 Accenture All rights reserved. 13
Case StudiesValue Delivered by Robotic Automation
Client Productivity ImpactTools Deployed Business Outcomes
Large Distribution
(Order Entry process)21 FTEsOCR
Large retail client
(Contract Management
@Client)
25% FTE reductionMashups
Large manufacturing
(Invoice Processing for
Single Line invoices PO
& Non-PO Automated)
30% FTE reductionMashups
Large retail client
(PTP, RTR and Store
Accounting)
28 FTEsRPA
Large Consumer
Goods
(Exit process
automation)
50% FTE reductionRPA
Large Retail client
(Order Entry Indexing)
• 52% reduction in transaction handling time (10.5mins to 5mins)
• Enables adherence to peak demand TAT SLA
• Elimination of defects due to manual entry
• 25% process automated
• Real Time TAT achieved
• BOI - Enabling sales team to focus on top line
• Potential new opportunities for @client
• 30% productivity benefit
• TAT Reduced to 1 Day (earlier 3 days)
• 100% Accuracy
• 30% Productivity Benefit
• Accuracy improved to 100%
• Transactional handling time reduced from 90 mins to 45 mins
• Improved DPA (Data Privacy Act) compliance
• Real Time TAT achieved
• with 100% accuracy20% FTE reductionMashups
Image Analytics
Copyright © 2015 Accenture All rights reserved. 15
Case Study: Auto Insurance Claims ProcessingKey Technology: Deep Learning
Computer science: The learning machines Nature News & Comment, 2014
Deep Learning: different layers of abstraction to replicate human cognition
Copyright © 2015 Accenture All rights reserved. 16
Case Study: Auto Insurance Claims ProcessingAutomated Classification of Car Damage Level
Classify if a car is
undamaged (new),
damaged or totaled
Problem Statement
• An Insurance Company wanted to automate claims processing using advanced machine learning technology, namely Deep Learning.
• When customers sent a picture of their damaged car, the Company would like to have the ability of automatically detect the level of
damage and use it to, for example, order spare parts and possibly detect fraud, if any.
• Accenture developed a Convolutional Neural Network algorithm (which belongs to the family of Deep Learning techniques) using a data
set of toy images.
•90% accuracy achieved.
• By automatically detecting level of damage, an Insurance Company saves on sending a human to assess the damage
• Apply the same technique for more use cases and other lines of businesses like Home Insurance with enhanced complexity and accuracy
For Auto Insurance, spare parts could be ordered automatically
For Home Insurance, evaluate building resistance, check if customers are telling the truth about additions to houses, identify multiple damages
Similarities/differences in damage patterns could be used to detect fraud
Value Delivered
Video Analytics
Copyright © 2015 Accenture All rights reserved. 18
Video AnalyticsSafety, Security, Operation and Marketing Insights
Application of Computer Vision to automate observation of video surveillance cameras, generating real time alerts
and detailed structured meta data for trend and anomaly detection
Singapore Safe City Oil Major Fuel Terminals French Police EventsFrench Telco
counting/conversion rate
Copyright © 2015 Accenture All rights reserved. 19
Example in Traffic Management
94.5%count accuracy
98.7%count accuracy
91.8%count accuracy
Copyright © 2015 Accenture All rights reserved. 20
Examples in an Airport
Copyright © 2015 Accenture All rights reserved. 21
Examples in Retail
Identity Analytics
Copyright © 2015 Accenture All rights reserved. 23
Case Study: UK BA, BAA – London AirportsSelf Clearance for EU ePassport Holders
Copyright © 2015 Accenture All rights reserved. 24
Case Study: Amsterdam SchipholSelf Clearance for EU ePassport Holders
Virtual Agents
Copyright © 2015 Accenture All rights reserved. 26
Virtual AgentsGoal: a Virtual Helpdesk Assistant that Interacts, Solves and Learns like a Human Agent
Communicates with the
customer using natural
language speech, online
chat and email…
Forwards a customer
query to another
department when
required…
Provides fact or
knowledge-based
answers to customer
queries when
appropriate...
Provides a resolution to a
customer query in a
variety of ways where
necessary…
Escalates to a supervisor
or another agent when
appropriate...
Understands the
customer's query or issue
and associated context...
Follows a specific process
or script to resolve a
customer query or issue
and can deviate from it
when appropriate…
Documents the customer
query and outcomes in the
ticket tracker system...
Disambiguates a
customer query by asking
clarifying questions when
required...
Accesses corporate back-
office systems to obtain
specific information or
triggers transactions when
required...
Performs offline tasks and
follow ups on a customer
query when required
Identifies and utilizes
pertinent data and
information specified by
the customer...
Asks for and utilizes
additional customer
documentation when
necessary
Learns new skills,
information an capabilities
through documentation,
training observation and
active discovery...
Copyright © 2015 Accenture All rights reserved. 27
• Phase I established the end-to-end flow where most customer enquiries
would be escalated to human agents and “observed”.
• Phase II increases the Customer Experience scope, to enable a virtual
agent to answer 25-35% of customer inquiries, including:
• Phase II also introduces Cognitive Robotics to access WQM (BMC
Remedy) to trigger events.
Currently Being Piloted at an Oil Services Company
Urgent Payment Requests (18%)
Invoice Statements (12%)
Missing Invoices –Not Due (8%)
OfflineProcesses and follow ups
Redirects (6%)
MySupplierPortal Access and Updates (3%)
Remittance Query (7%)
Where To?
Copyright © 2015 Accenture All rights reserved. 29
… 30 Years Ago
Ripped from the Headlines
Copyright © 2015 Accenture All rights reserved. 30
Accenture Technology Vision 2015Digital Business Era – Stretch Your Boundaries
www.accenture.com/technologyvision
Copyright © 2015 Accenture All rights reserved. 31
Workforce Re-ImaginedMore Effective, More Interesting
Copyright © 2015 Accenture All rights reserved. 32
Workforce Re-ImaginedBuilding Trust in Intelligent Systems
Copyright © 2015 Accenture All rights reserved. 33
• Cognitive technologies promise to automate or augment a wide range of work activities that today are largely done by humans, including manual workers and knowledge workers.
• Delivering business value from artificial intelligence requires understanding the nature of the work being done along two dimensions:
o Data Complexity: degree to which complex unstructured changing data needs to be taken into account
o Work Complexity: degree to which individuals need to apply their judgment and interpret a variety of information
Turning Artificial Intelligence into Business Value
Copyright © 2015 Accenture All rights reserved. 34
Turning Artificial Intelligence into Business Value – Healthcare
Copyright © 2015 Accenture All rights reserved. 35
Turning Artificial Intelligence into Business Value – Banking
Copyright © 2015 Accenture All rights reserved. 36
Technology-Rich
Business-Outcome Focused
People First Mindset
Creating an Artificial Intelligence Capability
Expert
Systems
Computer
Vision
Inference
EnginesMachine
Learning
Robotic
Process
Automation
Deep
LearningSensor
Processing
Knowledge
Repre-
sentationMini
Bots
Emotion
Recognition
Gesture
Recognition
Ontologies
Neural
Networks
Biometrics
Natural
Language
Processing
Video
Analytics
Copyright © 2015 Accenture All rights reserved. 37
Doing Things Differently
Doing Different Things
Artificial IntelligenceExponential Business Potential
Copyright © 2015 Accenture All rights reserved. 38
For More Information
Cyrille Bataller
Managing Director
Artificial Intelligence
@CyrilleBataller
Mobile: +33 6 85 54 24 14
www.accenture.com/aitechnology
#AI