Active in developing robotic solutions, Vanessa Evers (The Netherlands) is a professor of Computer Science at the Human Media Interaction group and Scientific Director of the DesignLab at the University of Twente. She has published almost 200 peer-reviewed publications, is an editor for the International Journal of Social Robotics and a senior editor of the Journal of Human-Robot Interaction.
Of robots and humans
For an artificial agent to assume a real social role and establish a meaningful relationship with a human, it would need to have a psychological, cultural, social and emotional profile. Current machine learning methods do not allow for such a development. Tomorrow's robots will be our humble assistants, nothing more.
We live in a time when robots clean our houses, drive our vehicles, disable bombs, provide prosthetic limbs, support surgical procedures, manufacture products, entertain, teach and surprise us. Just as smartphones and social media are offering a connectivity beyond anything we imagined, robots are beginning to offer physical capabilities and artificial intelligence (AI), cognitive abilities beyond our expectations. Together, these technologies could be harnessed to help solve important challenges, such as ageing societies, environmental threats and global conflict.
What will a day in our lives look like, in this not-so-distant future? Science fiction has explored these possibilities for centuries. Our lives will likely be longer: with synthetic organs to replace defective parts of our bodies, nanosized medical interventions allowing the precise targeting of diseases and genetics, and autonomous vehicles reducing fatalities in traffic. Our jobs will change dramatically. Certain jobs will not exist anymore and new jobs will emerge – in the development of robot service apps, for instance, that could run on available robot platforms in our homes. The way we are educated will also change radically – our senses and brains may be artificially enhanced, and our ability to reflect on new insights gained from the automated analysis of vast amounts of data will require a different treatment of information in schools.
But how will we relate to each other in a civilization that includes robots? In what way will we meet each other, have relationships and raise our children? To what extent will robots and humans merge?
Many of us wonder whether AI will become so intelligent and capable in human communication that the boundaries between human and artificial beings will blur. If it is possible to communicate in a natural way and build a meaningful interaction over time with an artificial agent, will there still be a divide in the relationships we have with people and technology? Also, once our human bodies and minds are enhanced with AI and robotics, what will it mean to be “human”?
From an engineering perspective, these advanced capabilities are still very far away. A number of hurdles need to be overcome. For now, robots and computers are completely dependent on a power source – they require a lot of electricity, and this complicates integrating robotic elements with human organic tissue. Another hurdle is the intricacy of human communication. While a one-off natural language conversation in a specific context with a robot can feel realistic, engaging people verbally and non-verbally over many conversations and contexts is quite another matter.
For example, when you call an artificial lost-and-found agent at an airport, a satisfying conversation is possible because there are only a limited number of goals the caller has. However, in creating a more extended relationship, for example, with a robotic pet, a much more complicated model must be developed. The robot needs to have internal goals, an extensive memory that relates experiences to various contexts, and it needs to develop these capabilities over time.
Through smart “tricks”, a robot can seem more intelligent and capable than it is – by introducing random behaviours which make the robotic pet interesting for longer, for instance. Humans have the tendency to “make sense” of the robot’s behaviours in a human way (we do this with animals too). However, in order to sustain a meaningful relationship which deepens and evolves over time, an extensive artificial inner life will need to be created.
How machines learn
A major hurdle in creating this rich artificial inner life is the way machines learn. Machine learning is example-based. We feed the computer examples of the phenomenon we want it to understand – for instance, when people feel comfortable. In teaching a machine to recognize this, data of people being comfortable is provided – this could be in the form of images, videos, their speech, heartbeat, social media entries, etc. When we feed videos to a computer, these are labelled with information on whether the people in it are comfortable or not – this may be done by experts in psychology, or in the local culture.
The computer uses machine learning to “reason” from these labelled videos to identify important features that correlate with feeling comfortable. This could be the body pose of a person, the pitch of their voice, etc.
Once the machine has identified the features predicting “comfort”, the resulting algorithm can be trained and improved, using different sets of videos. Eventually, the algorithm is robust and a computer with a camera can recognize how people feel with high, if not 100 per cent, accuracy.
Now that we understand roughly how machines learn, why is that a hurdle in creating a compelling inner life for an artificial agent to realize a seamless integration with humans?
Towards a complex synthetic profile
In order to develop an artificial agent that can have a sustained relationship, over a long period of time, with a person, we need the agent to have a compelling personality and behaviours, understand the person, the situation in which they are both in, and the history of their communication. More importantly, the agent would have to keep the communication going across a variety of topics and situations. It is possible to make a compelling agent, such as Amazon’s Alexa or Apple’s Siri, that you can speak to in natural language and have a meaningful interaction with, within the specific context of its use – set the alarm clock, make a note, turn down the heating, etc.
However, beyond that context of use, the communication quickly breaks down. The agent will find acceptable responses for a large variety of questions and comments, but will not be able to sustain an hour-long discussion about a complex issue. For instance, when parents discuss how to respond to their child not working hard at school, the conversation is very rich – they bring to it their understanding of the child, and their own personalities, emotions, history, socio-economic and cultural backgrounds, psychology, genetic make-up, behavioural habits and understanding of the world.
In order for an artificial agent to take on such a meaningful social role and develop a real relationship with a person, it would need to have a synthetic psychological, cultural, social and emotional profile. Also, the agent would need to learn over time how it “feels” and respond to situations in relation to this synthetic internal make-up.
This requires a fundamentally different approach to current machine learning. An artificially intelligent system that develops much like how the human brain develops, and that can internalize the richness of human experiences, is needed. The intricate ways people communicate with each other and understand the world is an unimaginably complex process to synthesize. The envisioned and currently available models of AI are inspired by the human brain or have elements of how the brain works, but are not yet plausible models of the human brain.
We already see AI achieving amazing feats – like reading the entire internet, winning at Go, the ancient Chinese board game, or running a fully automated factory. However, just like the English physicist Stephen Hawking (1942-2018) said he had only scratched the surface of understanding the universe, we are still merely scratching the surface of understanding human intelligence.
It won’t happen tomorrow
Robots and artificially intelligent systems will be able to offer us unique abilities to support and enhance our decision-making, understanding of situations and ways to act. Robots will be able to contribute to or autonomously carry out labour. Perhaps robotics will be fully physically integrated in our human bodies once a number of challenges are overcome. Also, we will relate to artificial agents as we do to humans – by communicating with them in natural language, observing their behaviours and understanding their intentions. However, in order to sustain a meaningful relationship with conversations and rituals, which deepen and evolve over time in the rich context of everyday life, as is the case between people, an extensive artificial inner life will need to be created. As long as we replicate or surpass certain functions of human intelligence rather than the holistic whole of human intelligence placed in the rich context of our everyday lives, it is unlikely that artificial agents and people can be totally integrated.