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Automation in the Age of Cognitive Computing Institute for Robotic Process Automation Automation in the age of cognitive computing Institute for Robotic Process Automation (IRPA) 7 December 2016 Loren Williams Chief Data Scientist and Artificial Intelligence Leader, Ernst & Young LLP, US AI has been around for awhile, but this time it’s different Deep learning 2010 ► Watson wins on Jeopardy 4 ► AlphaGo wins 3 out of 5 Expert systems 3 ► XCON Configurator 1980 ► Deep Blue chess match The Golden Age 1950 ► Turing test ► Dartmouth conference 2 The Ancients 1 ► Formal reasoning ► Mathematical logic Page 2 Automation in the age of cognitive computing What does Artificial Intelligence mean to us? Not this … Not this … But this … HAL 9000 Dolores, Westworld Automation system ► AI embodied in machine ► AI in a humanoid robot ► Interacts naturally, e.g., reads ► Communicates verbally ► Communicates verbally and and writes documents like ► General purpose, in context of non-verbally human, conversational mission ► Effectively human? ► Learns, i.e., becomes more effective through use and experience Image source: Skotcher Image source: HBO ► Fit to purpose Image source: Techipedia Page 3 Automation in the age of cognitive computing If AI is an automation system, how does it differ from Robotic Process Automation (RPA)? ► Unstructured Input ▬ Image, speech, text ▬ Search to Word2Vec ► Inferential ▬ Machine “learning” is statistical “estimation” ▬ Probabilistic outcomes ► Rapidly evolving Image source: Horses for Forces, July 2015 Page 4 Automation in the age of cognitive computing RPA is extremely disruptive… … because of a combination of lean deployment with Every reason to expect that the value clear benefits proposition is enduring Market in RPA professional services Accuracy Saving The right result, decision Low-risk or calculation the first time. potentials non-invasive Consistency Identical processes and 30%–50% tasks, eliminating Over offshore costs technology output variations. RPA can be overlaid on existing systems, allowing creation of a platform compatible with ongoing Audit trail Cross-industry developments in sophisticated Fully maintained logs RPA can be used across essential for compliance. algorithms and industries since it follows machine-learning tools. procedures in use. Productivity Freed-up human resources for higher value-added tasks. Right shoring Scalability Geographical independence Instant ramp up and down without business to match demand peaks case impact. and troughs. Duration Reliability Retention RPA projects run 9 to12 No sick days, services Shifts toward more months with a return of are provided 365 days a year. stimulating tasks. investment below 1 year. Page 5 Automation in the age of cognitive computing Cognitive Automation is equally disruptive and equally compelling ► The tasks that can be automated are high value Market growth expected to follow a similar work, done by highly paid humans trajectory ► “Artificial intelligence is now telling doctors how Market professional services related to cognitive computing to treat you,” - Wired, June 2014 ► “Artificial intelligence disrupting the business of law,” - FT, October 2016 ► “The robots are coming to Wall Street,” - NYT, February 2016 ► The information that can be ingested to drive the automation is vastly richer ► It can, and should, also be non-invasive to users Page 6 Automation in the age of cognitive computing web app web Decisions and automation Structured and unstructured output RPA portal Azure Information app service consumption Storage FlexRule Engine FlexRule services Cognitive Cortana Bot framework Cognitive RPA Engine RPA Cognitive Lake Azure Data Data factory Automationin the age of cognitivecomputing Database learning Machine Power Business Intelligence (BI) reporting (BI) Intelligence Business Power Azure SQL Azure a t a D n o i t s e g n i EY Data sources Data sources Structured data Business rules Unstructured data Page 7 Page RPA tool Ensemble solution Cognitive Automation: AI integrated in workflow automation Optical character Populate email recognition (OCR) Training Testing Write to output notifications notices Sourcing Digitizing Manual tagging Model testing Exception handling 2,000 Lotus Notes Lotus ► Route the non-extracted Mail Client email notices to humans Notes Tagging 2,000 Notices to extract data attributes for training set S3 Storage S3 Storage Machine learning Write to output OCR tuning ► Configure Machine Test 50–100 June notices to ► Write the data ► Validate results of Model using the data Validate success criteria for extracted from the OCR process and train it Cloud time saving provided by notices to a file Application ► Tune OCR ► Fine-tune Machine Machine Extraction parameters to Model Features improve quality Page 8 Automation in the age of cognitive computing Is it RPA, or is it CA? ► The process uses standard technology, with a very well understood interface ► There are multiple paths to successful resolution of the process; but the rules for choosing a path are clear ► It is a pervasive and time-consuming manual process, Page 9 Automation in the age of cognitive computing Page 10 Automation in the age of cognitive computing Convergence ► Traditional RPA will be deployed with AI technologies ► General purpose process automation tools will grow ► Special purpose AI systems will automate tasks and processes Image source: Brown Bird Design; Photo: Kenji Aoki https://www.wired.com/2013/04/convergence/ Page 11 Automation in the age of cognitive computing The human element: A critical success factor Technical capability often exceeds behavioral Lesson for cognitive automation alignment Behavioral alignment h ► Humans will train cognitive bots g (Analytics consumption) i H Technical Value ► Bulk training ► Culture and mental models capability gap creation ► Organization and process ► Reinforcement training design ► Learning and development ► Incentives and rewards Danger Behavioral ► Many cognitive bots will augment w zone alignment gap o work of humans L Low High Technical capability (Analytics production) ► Data science ► Data quality ► Infrastructure and tools Page 12 Automation in the age of cognitive computing Page 13 Automation in the age of cognitive computing EY | Assurance | Tax | Transactions | Advisory About EY EY is a global leader in assurance, tax, transaction and advisory services. The insights and quality services we deliver help build trust and confidence in the capital markets and in economies the world over. We develop outstanding leaders who team to deliver on our promises to all of our stakeholders. In so doing, we play a critical role in building a better working world for our people, for our clients and for our communities. EY refers to the global organization, and may refer to one or more, of the member firms of Ernst & Young Global Limited, each of which is a separate legal entity. Ernst & Young Global Limited, a UK company limited by guarantee, does not provide services to clients. For more information about our organization, please visit ey.com. Ernst & Young LLP is a client-serving member firm of Ernst & Young Global Limited operating in the US. © 2017 Ernst & Young LLP. All Rights Reserved. SCORE # - EYG no: 00048-173GBL ED None This material has been prepared for general informational purposes only and is not intended to be relied upon as accounting, tax or other professional advice. Please refer to your advisors for specific advice. ey.com.
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