Doing a Turing test

Turing-HarrisonFord

Recently I initiated an online chat with Apple support because I had a problem with my iPhone. The agent, Jayson, told me to turn the device off and on, but this didn’t fix the issue. Jayson then suggested I have the phone serviced by Apple, and arranged an appointment with the ‘technicians and geniuses’ in a local store. I thanked him and this exchange ensued:

Jayson
You’re most welcome! Thank you for your kindness, understanding & patience. Much appreciated John! Was I able to help you today?

Jayson
By the way ~ May you have a prosperous 2019!

John
Thanks for your help.  Bye now.

Jayson
I really appreciate you John, Don’t forget to eat your breakfast, lunch & dinner okay,? Its been my pleasure assisting you today, again my name is Jayson. Have a great day and take care always~

Jayson
All is well! You deserve the best in life and Cheers for a great 2019!

TuringTestRunning a very elementary Turing test on this dialogue reveals that Jayson is an artificial rather than human intelligence.  He (it) says things that no adult human agent would say in this situation. Yet Jayson’s mistakes are almost human, like those of a toddler learning to use language. He writes his own name phonically rather than conventionally. He can’t deal with my question – beyond the standard remedy of turning the device off and on – and so passes me on to the adult Apple technicians and geniuses. Unlike a traditional machine, he expresses affection and care: he wishes me a prosperous 2019 (in March) and reminds me to eat regularly, as his parents might have told him. No human programmer would make these mistakes; Jayson’s algorithm needs the capacity to adjust its warm, supportive language according to the season and the relationship.

Within a few years, it will become much more difficult to know whether one is ‘chatting’ to a human or machine agent (although we shall probably assume the latter). And this of course raises the question of the nature of knowledge: given appropriate technology, could a machine learn so adequately that the distinction between human learning – a activity of the embodied mind – and machine learning is elided? In Bladerunner 2049, there is no evident difference between the humans and the replicants. In Cultural Literacy (1988), E D Hirsch states that researchers in artificial intelligence have concluded that knowledge is the key component of all cognitive skills: ‘Once the relevant knowledge has been acquired, the skill follows’. Machine learning, according to this view, is not a mere simulacrum of human learning, but its paradigm.

This view clearly has very profound implications for educational policy, and aligns with current influential views on the teaching of language.

To be continued …

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Curriculum and assessment

The ongoing debate about student assessment now has an international dimension.  Owing in part to the agenda of the current Secretary of State for Education, comparisons are increasingly made between assessment systems in the UK and other countries.  The US system often gets a bad press in the UK because it is so dependent upon the judgement of the individual teacher.  Having worked in an California high school and as a moderator/examiner in the UK, I think the US system would have much to commend it — if a proper local system of moderation could be developed.  Local assessment, which becomes part of the teaching and learning process, is surely better than the spurious objectivity of a national “external” assessment system which (one hopes) could never be made to work in the US.  I want to quote a paragraph from the NATE  book text message:  the Future of A level English (2005), which emphasises the importance of a community of practice:

So how can curriculum, pedagogy and assessment best be integrated?  How might an effective community of practice be realised?  Clearly, the way forward is to recognise teachers’ expertise and experience in this area, and, by doing so, to acknowledge the usefulness of assessment in promoting teaching and learning as well as in measuring achievement.  Recognition of teachers’ roles in assessment also means giving credibility and status to this activity.  Logistically, if for no other reason, this is the only way forward, as the present system is unsustainable, even if it helps protect the Post Office from bankruptcy.  Validity and reliability could be achieved through the provision of regional networks (perhaps along the lines of the consortium system already run by the AQA) and through the accreditation of appropriate individuals and institutions.