Doing a Turing test


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:

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

By the way ~ May you have a prosperous 2019!

Thanks for your help.  Bye now.

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~

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 …

Children’s graves


Recently, a dear friend visited for a few days.   During our first evening, when we were discussing what to do during her visit, she mentioned St George, a suburb of Bristol nearby. I asked her what her connection with this area was. After a brief pause, she told me that her first child, who had died at birth, had been interred in the Avonview Cemetery. At the time (fifty-two years previously), the hospital usually made arrangements, and the boy’s ashes had been scattered on open ground within the cemetery, overlooking the city.   My friend had been back to the spot many years before, but she felt that it would be fitting to return again.

The next day, we went to the cemetery.   As she remembered, it was very large and quite elevated. The taxi driver left us at the main entrance, and we walked up the long drive. Graves addressed us on all sides, mostly neglected and overgrown, some with broken memorials or paving. Some of the headstones had been laid flat on the ground for reasons of safety.

We turned left along a higher path.   I didn’t know whether my companion had any sense of the right direction, but after a while she turned through a gate into a small area behind a wall. This was the children’s graveyard.   The area was less than an acre in size, full of small graves, mostly stone and gravel, with vases containing flowers or colourful windmills. Children’s toys – usually figures of animals – were placed on many of the graves. The inscriptions on the graves revealed that in nearly every case the child’s life had lasted less than one day. Every one was maintained, most of them immaculately. A young couple were tending a grave not far from where we stood.

I found the sight almost unbearably moving, and stayed in the children’s graveyard while my friend continued to search for the spot where her child’s remains had been scattered. Why, I wondered, do we take such care with the memory of children whose lives ended almost before they began? It must be to do with the sense of lost potential, of unfairness. The adults commemorated by the broken graves in the main area had lived their lives. But these children had died before their parents. They had never had the chance to contribute to life, to receive love from others and to give their joy. Continuity was possible only symbolically. Their memorials would be maintained as freshly as the day they were created.

I understood, as I waited in the children’s graveyard, why the loss of a younger person is so devastating.   It is against the order of nature.   It represents the loss of the youthful virtue that refreshes and renews. Whether the loss is of one’s own child, a younger partner, or perhaps a young friend or relative, its poignancy is different from that of a deceased older than oneself who has lived out their life span.

My friend returned to tell me that she had found the place. It was, as she remembered, an open, grassy, gently-sloping hillside. It was the common ground, unmarked. There was no broken, neglected stone. A carpet of daisies formed a wide path down the hill.  Buttercups burst their deep yellow out of the long grass. Bright flowers had been tied to a young tree, in remembrance.

She stood in the field.

Afterwards, we walked to the main road, shared a lunch in a wholefood café, and caught the local train home.