To Siri With Love - how chatbots are becoming social companions and teachers...

The New York Times carried a heartwarming story "to Siri With Love" by a mother who had an autistic son, Gus. Siri was a Godsend, as it never tired of answering his questions. Far from isolating Gus, Siri was a companion and lifeline. His mother was grateful as it helped both herself and Gus deal with his condition. Gus started to articulate more clearly to be understood and Siri proved to be a non-judgemental friend and teacher. Chatbots are starting to appeal to more and more of us. They are an integral part of the social landscape.
So there’s a new kid on the block….

Social bots

There is an assumption that ‘social’ in learning, always means one human being talking to another or others. That could be synchronously, face-to-face, telephone, webinar and so on, or asynchronously online through social media, chat and so on. But this is to miss a trick. Increasingly, we will have bots as part of our social networks. They may be bots delivering a specific service or learning experience. We have finance bots delivering personal financial services from your bank. Health bots dealing with your health and no end of customer care bots. The fact that they are not people does not mean they are not part of our social network.

We have ample evidence from Nass and Reeves (The Media Equation), that we anthropomorphise technology and bots in particular have been shown to successfully ‘pass’ for humans, thereby passing the Turing test.  The Georgia Tech tutor bot not only passed this test, the students put it up for a teaching award. Google Duplex has successfully executed bot calls to a restaurant and hairdressers, completing appointments. Bots in general, whether useful, benign or malicious, are now part of our social networks.

Ecosystem

In fact, we have every reason to expect that they will play an increasing role in our social ecosystem, as dialogue and voice play a greater role in human-machine interaction. They are already in our homes through Alexa, Google Home and other devices. Sex robots are essentially bots inside robot bodies. We make calls to bots on the telephone. But mostly, we encounter bots online. A recent Pew study followed Twitter activity and identified surprising levels of bot activity:

1. Two-thirds (66%) of all tweeted links were shared by suspected bots. 

2. Suspected bots also accounted for 66% of tweeted links to sites focused on news and current events.

3. Among news and current events sites, those with political content saw the lowest proportion (57%) of bot shares.

4. About nine-in-ten tweeted links to popular news aggregation sites (89%) were posted by bots, not human users.

5. A small number of highly active bots were responsible for a large share of links to prominent news and media sites.

This raises interesting questions about our awareness of bots and their influence.

Bots and learning
In learning, however, bots are, for the moment, in a controlled environment. At work bots, such as Otto, pop up within workflow tools, such as Slack, Microsoft Teams and Facebook at Work. In learning, we have bots that increase student engagement, bots that provide learner support, tutorbots, mentorbots, assessment bots and wellbeing bots. These bots are guided learning bots, with limited capabilities but that often matches the need to stick to a guided learning path or defined domain in learning. Structure and focus in learning is often useful.

As the technology progresses, they will get smarter with the capability to sustain dialogue, retain memories of all previous conversations, be sensitive to content and become more personal. They will play an increasing role in engagement, support and delivery. This will happen in a piecemeal fashion but who knows, in time they may master the skills necessary to be a good teacher or trainer.

The learning game used to be simple. We had teachers and learners. Sure, teachers learnt from other teachers and learners. Learners learnt from teachers and other learners. Now we have these interlopers who can both teach and learn. Machine learning allows bots to learn – very quickly. We have seen their success in chess, Go and Poker. Increasingly, they are mastering other human activities. The fact htat modern AI techniques allow them to play themselves millins of times in a very short ;period of time or even set them selves up to be adversarial, leading to rapid improvement and competence is what’s new in AI. Machine learning, Reinforcement learning and Generative Adversarial Networks, and many other variants of ‘learning’ methods are driving the success of AI. Social learning networks now have these new entrants – bit learners that learn fast.

Anonymity

This raises several questions. Should anonymous bots be allowed? Bots are not conscious, even cognitive. They mimic human behaviour and in this sense fool the user into thinking they are human or have human qualities. They are faking it. There is an argument for not allowing anonymous bots, as they break the trust one assumes in dialogue, that the other agent is a real person with moral responsibilities, not a piece of software with no moral sense. Alternatively, we could see this in purely utilitarian terms and see the advantages purely in terms of outcomes – better teaching and learning.

On the other hand, the ‘anonymity’ of bots can be their cardinal advantage. I spent ten days on the wellbeing bot ‘woebot’. Its advantage is its anonymity. Few young people will want to admit to their teacher, lecturer or adult that they are having mental health problems, due to fear and embarrassment. Many will feel more comfortable dealing with a helpful, anonymous bot.

Bias

One could argue they are a conduit for bias. This could be true in news aggregation but I doubt that this is much of a problem in learning. All humans are biased, and while bots can embody intended or unintended bias, this can be eliminated. Kahneman who got the Nobel Prize for his work in this area, describes human bias as uneducable. In practice, I think that bots can easily eliminate gendered language, confirmation bias, anchoring and many other biases that seriously distort educational and learning goals. This may be our best bet in eliminating the huge amount of bias that exists within the system.

Living with bots

The bots are here. At present, they are child-like, narrow in domain and capabilities but nevertheless useful. We must learn to live with them. In a sense, bots have always been around. When I read a novel, the narrator and characters are essentially agents that have fooled my imagination into thinking they are real people. We have no problem in reading fact or fiction from the past, even from dead authors but still see them as being in the moment, when they address us in their texts. What gives computer bots extra potency is their seeming, living presence and adaptability. They respond, answer back, ask us things and get personal. Increasingly they are the mediators. But that’s essentially what teaching is – mediation. 

Bots and social constructivism

Strangely enough it is the social constructivists, led by Vygotsky, who should celebrate bots the most. If knowledge is the internalisation of social activity, then bots are a constructivists wet dream. It fits with Bandura’s Social Learning Theory, where one leans through social observation and modelling. I don’t buy this theory LINK but it is interesting to me that the most vociferous anti-technology critics, who rely on a theory of social learning, may be sabotaged by technology that plays their game. If they are social agents, why not exploit them to the full.

Conclusion

What bots can and will do, is scale social learning. They don’t sleep eight hours a day, get distracted and bored. They can also download, network and learn from both us and themselves. And they never die – they only get better.