eXplainable Predictive Decisioning: combine ML and Decision Management to promote trust on automated decision making
Presented by: Daniele Zonca & Matteo Mortari, Red Hat Presented at All Things Open 2020 Abstract: The increased demand for transparent, explainable decision making, that is accurate, consistent and effective, has never been greater. Legislations like GDPR are just a result of increasing concerns about privacy, safety and transparency in general. While AI/ML solutions are great at making sense of high volumes of data, the reasoning process for most of the generated analytic models is usually quite opaque. Decision Management on the other hand, is a discipline that aims to provide full transparency on the decision process, but requires formalization of knowledge into decisions/rules, using some form of knowledge engineering (automated or not). During this presentation, attendees will learn about a standards based, pragmatic approach to achieve the goals of eXplainable AI (XAI), combining decision models and analytic models. The approach promotes an effective method to increase transparency on automated decision making, without losing effectiveness. In particular, presenters will demo how PMML (Predictive Modelling Markup Language), a well established standard for the representation of predictive models generated using Machine Learning can be transparently combined with DMN (Decision Model and Notation), a Decision Modeling standard that defines a high level language for decision automation. Attendees will have the opportunity to learn how the combination of these two Standards enhances and creates a high level effective solution for AI which can be explained and trusted.
![AI researchers predict that Pure AI has a 50%
chance of being achieved in 125 years
Source: “When Will AI Exceed Human Performance? Evidence from AI Experts”, arXiv:1705.08807v3 [cs.AI] 3 May 2018
eXplainable Predictive Decisioning
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eXplainable Predictive Decisioning: combine ML and Decision Management to promote trust on automated decision making
- 1. 1 Combine ML and Decision Management to promote trust on automated decision making Daniele Zonca Architect Red Hat Decision Manager eXplainable Predictive Decisioning Matteo Mortari Senior Software Engineer Red Hat Decision Manager
- 2. AI researchers predict that Pure AI has a 50% chance of being achieved in 125 years Source: “When Will AI Exceed Human Performance? Evidence from AI Experts”, arXiv:1705.08807v3 [cs.AI] 3 May 2018 eXplainable Predictive Decisioning 2
- 3. Pragmatic AI is a set of building block technologies Natural Language Processing Machine Learning Robotics Maths Optimization Digital Decisioning eXplainable Predictive Decisioning 3
- 4. AI = + + Extract information from data analysis Model the human knowledge and expertise Solve complex problems to better resources allocations + + eXplainable Predictive Decisioning 4 Pragmatic Approach to Predictive Decision Automation Machine Learning Digital Decisioning Maths Optimization Ref: Forrester Research, Inc., “The Future of Enterprise AI and Digital Decisions”, BRAIN 2019, Bolzano Rules and Artificial INtelligence Summit Sep 2019
- 5. PMML (1999) DMN (2015) Business Automation Machine Learning BPMN2 (2011) CMMN (2014) Connecting Business Automation and Machine Learning FOCUS OF THIS PRESENTATION eXplainable Predictive Decisioning 5
- 6. Benefits of an integrated, standards-based solution Data Scientists Decision Modelers Build the predictive models (PMML) Develop Decision Models ❏ Direct consumption of predictive models in decision models ❏ No translation needed ❏ Supports all 19 executable models from PMML (Score cards, Neural nets, Regression, Random Forest, etc) ❏ Open the AI box - helps with transparency and explanation ❏ Direct collaboration between Data scientists and Decision Modelers ❏ Enables event correlation and consolidation - KPI monitoring eXplainable Predictive Decisioning 6
- 7. Use cases ❏ Efficient Customer Service Management - best next action for representatives ❏ Predictive Customer Retention ❏ Upsell appropriate new products ❏ Fraud detection ❏ Customer loyalty scoring ❏ Optimized workforce management ❏ Personalized experience ❏ ... eXplainable Predictive Decisioning 7
- 8. Predictive Decision Automation - Overview eXplainable Predictive Decisioning 8
- 9. A case to manage disputes Invoking a Decision Service BPMN Model eXplainable Predictive Decisioning 9
- 10. The Past: determine risk analytically via Decision Table eXplainable Predictive Decisioning 10
- 11. A better alternative today: determine risk via ML predictors Machine Learning Business Data Images, Unstructured docs Documents Predictive Model car_holder_risk_regression.pmml Let’s integrate ML inside of the decision model ! eXplainable Predictive Decisioning 11
- 12. A Decision Service to automate low risk disputes Leveraging Predictive Models DMN Model eXplainable Predictive Decisioning 12
- 13. Using Predictive Models in DMN 1. Choose the PMML file 2. Choose the model within the file 3. Editor automatically shows the parameters the model expects eXplainable Predictive Decisioning 13
- 14. Testing DMN models that use Predictive Models Set the input values Check expected values Each row is a test eXplainable Predictive Decisioning 14
- 15. Monitor Processes and Decisions Create custom dashboards Compare model results View Business Metrics, including predictive model results eXplainable Predictive Decisioning 15
- 16. eXplainable Predictive Decisioning Demo Scenario Architecture Credit Card Dispute System Banking Application (Dispute UI) Business UI/App Client UI/App App Engine Customer Red Hat Process Automation Manager Case Models OpenShift Container Platform Grafana (dashboards) Prometheus Decision Models Business User Decision Server Decision Engine Metrics Process Engine Predictive Models Author Test Deploy Manage Business Analyst 16
- 17. Resources https://youtu.be/zaTw1c5-47c https://youtu.be/EVXp2q_8yFw Drools featuring DMN support - https://drools.org/learn/dmn.html Learn DMN - http://learn-dmn-in-15-minutes.com Kogito - http://kogito.kie.org/ TrustyAI introduction: https://blog.kie.org/2020/06/trusty-ai-introduction.html TrustyAI aspects: https://blog.kie.org/2020/06/trusty-ai-aspects.html Red Hat Business Process Automation: https://www.redhat.com/en/products/process-automation eXplainable Predictive Decisioning 17
- 18. linkedin.com/company/red-hat youtube.com/user/RedHatVideos facebook.com/redhatinc twitter.com/RedHat 18 Red Hat is the world’s leading provider of enterprise open source software solutions. Award-winning support, training, and consulting services make Red Hat a trusted adviser to the Fortune 500. Thank you