AI as a Knowledge Management Approach

1. AI as a Knowledge Management Approach John Kingston

2. Knowledge management is… • Getting the right knowledge to the right people in the right format in the right place at the right time

3. Knowledge based systems • Are an application of (cognitive) AI • Contain expert knowledge • Make it available to non-expert users where they work • Make it available by asking them questions • And then making their own decisions • And possibly justifying them • Conclusion: KBS are a knowledge management approach

4. RAF Expert Provisioner • Domain: Logistics (ordering spare parts) • Knowledge: Understanding the implications of various numbers on the order form • E.g. A ‘1’ in ‘Disposed of’ meant ‘Obsolete item – remaining stocks have been sent to the organisation that dispose sof obsolete items for the best price • So before re-ordering any, phone the disposals organisation! • Estimated saving: £30 million p.a.

5. EASE • Estimation and Assessment of Substance Exposure • Helps HSE inspectors estimate the exposure levels for substances in newly introduced industrial processes • Helped standardise the UK approach to this assessment throughout Europe

6. General Electric: Case Based Reasoning Some more recent examples, from GE: • Call centre automation: saves estimated $60m p.a.; • Remote diagnostics for locomotives; • Aircraft engine monitoring; • Colour matching for plastics; • Property valuation. • See http://best.berkeley.edu/~goebel/publications_files/FLAIRS_01_r.pdf

7. What type of knowledge is appropriate for management using AI? It’s actually easier to answer the question, “What type of tasks are appropriate?” • Classification • Diagnosis • Assessment • Monitoring • Configuration • Design • Planning • Scheduling Another key heuristic: Could the expert solve the problem over the telephone, if necessary? • Symbolic vs numerical/geometric/perceptual knowledge

8. Other approaches to knowledge management • ‘Connect’ approaches: • Communities of practice • Apprenticeship/mentoring • Seminars • “Speed dating” events: knowledge cafes, knowledge marketplaces, peer assists • Ask the expert • Knowledge portals • ‘Collect’ approaches: • Wikis • Lessons learnt databases • Records of knowledge capture interviews

9. What other factors make an AI approach to KM appropriate? • Number of people who need the knowledge: >50 • AI systems are relatively expensive to produce, but greatly reduce the demands on experts’ time • There is a high turnover of staff • A standardised approach to the task is desirable • And/or the knowledge must be carefully verified and validated before being disseminated • If innovation (‘new’ solutions) are likely, consider case based reasoning • The task is too difficult/has to be performed too quickly for even a human expert to perform optimally • The task takes the expert between 3 minutes and an hour to perform

10. Summary • Knowledge based systems use a ‘cognitive’ AI approach to distribute knowledge to those who need it • Capable of saving significant sums of money • Higher investment required than for other KM techniques • Careful selection of an appropriate task is advisable