Knowledge Infrastructure

In this article, we outline the concept of knowledge infrastructure and describe how it differs from Information Technology (IT) infrastructure, with particular regard to the implications for education theory, practice and policy. We examine the inherent limits to growth for attempts to handle knowledge, as opposed to information, via the types of software and hardware likely to be available in the next few decades. We show how a simple process model can be used to identify pinch points where knowledge, as opposed to information, is a bottleneck. We also show how a simple model of knowledge types and knowledge locations can be combined with the process model to remove those bottlenecks via existing low-cost technology and a more efficient use of existing human expertise. We conclude that a minimal investment in knowledge infrastructure would provide significant human, social and economic benefits, by creating major added value from existing digital and organisational infrastructure.

Content

Author and article information

Contributors

Gordon Rugg

Colin Rigby

Sue Gerrard

Amy Martin

Jennifer Skillen

Emma Bonfiglio

Allison Gardner

Yuxin Guo

Shailey Minocha

Gavin Taylor

Conference

Publication date: July 2022

Publication date (Print): July 2022

Pages: 1-9

Affiliations

[0001]Hyde & Rugg Associates

Market Drayton, UK

[0002]Keele University

Keele, UK

[0003]A.G. Telehelmets

Market Drayton, UK

[0004]Honeywell UK

Horsham, UK

[0005]Open University

Milton Keynes, UK

[0006]Weavers Academy

Wellingborough, UK

Article

DOI: 10.14236/ewic/HCI2022.20

SO-VID: ab77d898-5d77-4d80-9d28-29fe3a6acbef

License:

This work is licensed under a Creative Commons Attribution 4.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/

Conference name: 35th International BCS Human-Computer Interaction Conference

Conference acronym: HCI2022

Conference number: 35

Conference location: Keele, Staffordshire

Conference date: July 11th to 13th, 2022

Conference sponsor: Electronic Workshops in Computing (eWiC)

Conference theme: Towards a Human-Centred Digital Society

History

Product

1477-9358 BCS Learning & Development

Self URI (article page): https://www.scienceopen.com/hosted-document?doi=10.14236/ewic/HCI2022.20

Self URI (journal page): https://ewic.bcs.org/

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Comments

Comment on this article

[1] Anon (2021) Write a business plan.

[2] Available at: https://www.gov.uk/write-business-plan (accessed 16 May, 2021).

[3] Avison, D. and Fitzgerald, G. (2003) Information Systems Development: Methodologies, Techniques and Tools (3^rd edition). McGraw-Hill, London.

[4] Boyd, B. (2016) Popper’s World 3: Origins, Progress, and Import. Philosophy of the Social Sciences 46(3): 221–241.

[5] Dampney, C.N.G, Busch, P. and Richards, D (2002) The meaning of tacit knowledge. Australasian Journal of Information Systems, Special Issue, January 2002. Cited in: Stair, R.M. and Reynolds, G.W. (1998). Principles of Information Systems: A Managerial Approach (3rd edition). Boyd and Fraser, Danvers, Mass.

[6] Davenport, T. and Fitts, J. (2021) AI Can Help Companies Tap New Sources of Data for Analytics. Harvard Business Review, March 19, 2021.

[7] de Groot, A.D. (1965) Thought and Choice in Chess. Mouton, the Hague.

[8] Eeuwen, M.V. (2017) Mobile conversational commerce: messenger chatbots as the next interface between businesses and consumers (Master's thesis, University of Twente).

[9] Forsyth, R. (1981) BEAGLE: A Darwinian Approach to Pattern Recognition. Kybernetes 10: 159–166.

[10] French, R.M. (2012) Moving beyond the Turing Test. Communications of the ACM, 55:12.

[11] Gigerenzer, G. (2008) Gut Feelings: Short Cuts to Better Decision Making. Penguin, London.

[12] Griol, D., Carbó, J. and Molina, J.M. (2013) An automatic dialog simulation technique to develop and evaluate interactive conversational agents. Applied Artificial Intelligence, 27(9), pp. 759-780.

[13] Guo, Y. (2019) A business evaluation chatbot (be-bot) acting as an interactive virtual agent prototype. Unpublished undergraduate dissertation, Keele University, UK.

[14] Hassabis, D. (2017) Artificial Intelligence: Chess match of the century. Nature 544: 413–414.

[15] Hinkle, D. (1965) The change of personal constructs from the viewpoint of a theory of construct implications. PhD Thesis, Ohio State University, USA.

[16] Kahneman, D., Slovic, P. & Tversky, A. (Eds.) (1982) Judgement under uncertainty: Heuristics and Biases. Cambridge University Press, Cambridge.

[17] Knight, W. (2016) An AI with 30 years worth of knowledge finally goes to work.

[18] https://www.technologyreview.com/2016/03/14/108873/an-ai-with-30-years-worth-of-knowledge-finally-goes-to-work/ (accessed May 2021).

[19] Lenat, D., Prakash, M., and Shepherd, M. (1986) CYC: Using Common Sense Knowledge to Overcome Brittleness and Knowledge Acquistion Bottlenecks. AI Magazine 6(4): 65–85.

[20] Lo Bello, L. Mariani, R., Mubeen, S. and Saponara, S. (2019) Recent Advances and Trends in On-Board Embedded and Networked Automotive Systems. IEEE Transactions on industrial informatics, 15(2) 10038-10051.

[21] Maiden, N.A.M. and Rugg, G. (1996) ACRE: a framework for acquisition of requirements. Software Engineering Journal 11, 183–192.

[22] Norman, D. (2013) The Design of Everyday Things (revised and expanded edition). The MIT Press, London.

[23] Polanyi, M. (1967) The Tacit Dimension. Routledge and Kegan Paul, London.

[24] Quinlan, J.R. (1986) Induction of Decision Trees. Machine Learning 1(1): 81–106.

[25] Ramsetty, A. and Adams, C. (2020) Impact of the digital divide in the age of COVID-19. Journal of the American Medical Informatics Association, 27(7): 1147–1148.

[26] Reynolds, T.J. and Gutman, J. (1988) Laddering theory, method, analysis, and interpretation. Journal of Advertising Research 28: 11–31.

[27] Rugg, G. and McGeorge, P. (1995) Laddering. Expert Systems 12: 339–346.

[28] Shawar, B.A. and Atwell, E. (2007) Chatbots: are they really useful?. Ldv Forum 22(1) pp. 29-49).

[29] Shortliffe, E.H. and Buchanan, B.G. (1975) A model of inexact reasoning in medicine. Mathematical Biosciences 23(3–4): 351–379.

[30] Skillen, J.D. (2017) The symptom matrix: Using a formalism-based approach to address complex syndromes systematically. Musculoskeletal Care 15, 253–256.

[31] Skillen, J.D. (2019) The Friends and Family Test: From card sorts to control charts. Methodological Innovations. 12(2).

[32] Standage, T. (1998) The Victorian Internet: The Remarkable Story of the Telegraph and the Nineteenth Century's On-Line Pioneers. Walker and Co, London.

[33] Steger, C, Ulrich, M and Wiedemann, C (2018) Machine Vision Algorithms and Applications (2nd ed.). Weinheim: Wiley-VCH.

[34] Weizenbaum, J. (1976). Computer Power and Human Reason: From Judgment to Calculation. W. H. Freeman and Company, New York.

[35] Werbos, P. (1982) Applications of advances in nonlinear sensitivity analysis. In: Drenick, R.F., Kozin, F. (eds) System modeling and optimization. Springer, London pp 762–770.

[36] http://werbos.com/Neural/SensitivityIFIPSeptember1981.pdf (accessed 2 March, 2020).

[37] Wootton, D. (2015) The invention of science: A new history of the scientific revolution. Penguin, Harmondsworth.

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