May 16, 2019 04:44 AM
Is a Robot just another "Animal"?
https://news.cnrs.fr/opinions/is-a-robot...her-animal
EXCERPT: Artificial intelligence algorithms are often seen as 'black boxes' whose rules remain inaccessible. [...] Understanding the behaviour of intelligent machines is a broader objective than understanding how they are programmed. Sometimes a machine's programming is not accessible, for example when its code is a trade secret. In this case, it is important to understand a machine from the outside, by observing its actions and measuring their consequences. Other times, it is not possible to completely predict a machine’s behaviour based on its code, because this behaviour will change in a complex manner when the machine adapts to its environment through a learning process, guided but ultimately opaque. In this case, we need to continually observe this behaviour, and simulate its potential evolution. Finally, even when we can predict a machine’s behaviour based on its code, it is difficult to predict how the machine's actions will affect the behaviour of humans (who are not programmable), and how human actions will in turn change the machine's behaviour. In this case, it is important to conduct experiments in order to anticipate the cultural coevolution of humans and machines.
[...] A new scientific discipline dedicated to machine behaviour is needed to meet these challenges, just as we created the scientific discipline of animal behaviour. We cannot understand animal behaviour solely on the basis of genetics, organic chemistry, and brain anatomy; observational and experimental methods are also necessary, such as studying the animal in its environment or in the laboratory. Similarly, we cannot understand the behaviour of intelligent machines solely on the basis of computer science or robotics; we also need behaviour specialists trained in experimental methods from the fields of psychology, economy, political science, and anthropology.
[...] By bringing together what is currently dispersed, we will enable researchers in machine behaviour to identify one another and cooperate across disciplinary boundaries. We will also make it easier for public authorities and regulatory agencies to rely on a scientific corpus that is scattered and difficult to access today, and for citizens to more clearly position themselves in a world disrupted by the emergence of intelligent machines. We cannot perfectly predict the behaviour of robots that are continuously learning from their interactions with their environment. Jean-François Bonnefon believes we must create a science of machine behaviour in order to observe them experimentally. That is the objective behind an appeal to researchers, public decision makers, and intelligent machine manufacturers that I recently published in the journal Nature with 22 European and American co-authors... (MORE)
Ethical and social implications of embodied AI in mental health care
https://www.news-medical.net/news/201905...-care.aspx
INTRO: Interactions with artificial intelligence (AI) will become an increasingly common aspect of our lives. A team at the Technical University of Munich (TUM) has now completed the first study of how "embodied AI" can help treat mental illness. Their conclusion: Important ethical questions of this technology remain unanswered. There is urgent need for action on the part of governments, professional associations and researchers.
Robot dolls that teach autistic children to communicate better, computer-generated avatars that help patients cope with hallucinations, and virtual chats offering support with depression: Numerous initiatives using embodied AI for improving mental health already exist. These applications are referred to as embodied because they involve interactions between individuals and an artificial agent, resulting in entirely new dynamics. (MORE)
https://news.cnrs.fr/opinions/is-a-robot...her-animal
EXCERPT: Artificial intelligence algorithms are often seen as 'black boxes' whose rules remain inaccessible. [...] Understanding the behaviour of intelligent machines is a broader objective than understanding how they are programmed. Sometimes a machine's programming is not accessible, for example when its code is a trade secret. In this case, it is important to understand a machine from the outside, by observing its actions and measuring their consequences. Other times, it is not possible to completely predict a machine’s behaviour based on its code, because this behaviour will change in a complex manner when the machine adapts to its environment through a learning process, guided but ultimately opaque. In this case, we need to continually observe this behaviour, and simulate its potential evolution. Finally, even when we can predict a machine’s behaviour based on its code, it is difficult to predict how the machine's actions will affect the behaviour of humans (who are not programmable), and how human actions will in turn change the machine's behaviour. In this case, it is important to conduct experiments in order to anticipate the cultural coevolution of humans and machines.
[...] A new scientific discipline dedicated to machine behaviour is needed to meet these challenges, just as we created the scientific discipline of animal behaviour. We cannot understand animal behaviour solely on the basis of genetics, organic chemistry, and brain anatomy; observational and experimental methods are also necessary, such as studying the animal in its environment or in the laboratory. Similarly, we cannot understand the behaviour of intelligent machines solely on the basis of computer science or robotics; we also need behaviour specialists trained in experimental methods from the fields of psychology, economy, political science, and anthropology.
[...] By bringing together what is currently dispersed, we will enable researchers in machine behaviour to identify one another and cooperate across disciplinary boundaries. We will also make it easier for public authorities and regulatory agencies to rely on a scientific corpus that is scattered and difficult to access today, and for citizens to more clearly position themselves in a world disrupted by the emergence of intelligent machines. We cannot perfectly predict the behaviour of robots that are continuously learning from their interactions with their environment. Jean-François Bonnefon believes we must create a science of machine behaviour in order to observe them experimentally. That is the objective behind an appeal to researchers, public decision makers, and intelligent machine manufacturers that I recently published in the journal Nature with 22 European and American co-authors... (MORE)
Ethical and social implications of embodied AI in mental health care
https://www.news-medical.net/news/201905...-care.aspx
INTRO: Interactions with artificial intelligence (AI) will become an increasingly common aspect of our lives. A team at the Technical University of Munich (TUM) has now completed the first study of how "embodied AI" can help treat mental illness. Their conclusion: Important ethical questions of this technology remain unanswered. There is urgent need for action on the part of governments, professional associations and researchers.
Robot dolls that teach autistic children to communicate better, computer-generated avatars that help patients cope with hallucinations, and virtual chats offering support with depression: Numerous initiatives using embodied AI for improving mental health already exist. These applications are referred to as embodied because they involve interactions between individuals and an artificial agent, resulting in entirely new dynamics. (MORE)