The man and the machine manifesto
Blog: End to End BPM
“Self-organised systems, lie all around us. There are quagmires, the fish in the sea, or intractable systems like clouds. Surely, we can make these work things out for us, act as our control mechanisms, perhaps most important of all, we can couple these seemingly uncontrollable entities together so that they can control each other. Why not, for example, couple the traffic chaos in Chicago to the traffic chaos in New York in order to obtain an acceptably self-organising whole? Why not associate brains to achieve a group intelligence?”
Gordon Pask, The natural history of networks
Today there is a shadow or sense of doubt if we as humans want machines to think or to do – some people already argue they do think, detached from the consciousness bond – and it would replace humanity soon, as many others advocate singularity is near with systems that can adapt themselves, command, control other systems, something as Douglas Hofstadter referred to “tangled recursion” as an example of machine intelligence.
I ultimately believe that humans and powered AI machines will work together, not compete against each other. Humans will be much more empowered by the symbiotic combination of machine work, meaning that we will need to continuous to adapt to rather than become indispensables, we increase our own capabilities.
However, there are many untamed challenges in terms of such man and machine symbiosis, as we the human species, have the responsibility to define by which rules we want to live, as machines progress in new areas, changing the foundations on our society is organized, as per bellow.
Governance
Much has been discussed how to define machine design rules and relevant regulation. Some experts believe that is the hands of humans to define such rules and while machines are tightly controlled by humans we can define how machines should be engineered. However, some examples related with war machines, demonstrate that Isaac Asimov’s laws do not apply anymore, once the potential for harm is increasing rapidly.
Hence the challenge stands. Consider the scenario of an intelligent medical system that provides counselling and advisory, induces a medical doctor with error. Who is responsible? The Doctor? The system? The entity that conceived the system? The trainer that trained the system to make decisions, based on a knowledge base? How do we deal with human life loss? Regulatory bodies for the engineering profession or other domain expertise, have clearly defined rules for design or professional act decisions, made by humans, however, in terms of machines endowed with any kind of intelligence, governance appears missing and there is no common broad agreement.
Societal impact, innovation and economy growth
There is no doubt that technology was always the common denominator that sparked economic growth, the press, steam engines and lastly the internet, created in three different moments in time tectonic shifts. However, prosperity also contributes to unemployment. Technology tends to automate at scale and replace repetitive tasks, but the last wave of technological developments is already targeting knowledge workers as well. Hence, the challenge is not related with low income workers only. The balancing act should be how the use of technology can contribute to higher living standards, diminish inequality and drive inclusion.
Human and Machine Interface
Mixed reality is becoming a popular interface in human-computer interaction for combining virtual and real-world environments, and it has recently been a common technique for human-robot interaction, it price is however a barrier for adoption and creates digital imparity. Natural language processing is becoming another de-facto interface, applied for example on business to consumer interactions, but some questions are still not addressed in terms of humans that speak a language blending influence of their own culture that a machine is not aware of. Despite the advance interacting with devices like smartphones, as technology progresses, it is relevant do involve interface designers to make a reflection how machines affect human to human interactions and human to machine interactions.
Ethics
Tackling the trade-off between privacy and security is today already a challenge, related to the fundamental but complex separation between what constitutes the private and the public space of an individual. The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in another can be condemned. The concept of privacy is constantly being redefined to a point that can be transform into a matter of transparency, for example, sharing publicly your taxes declarations if you are a politician. How we deal with ethics in terms of a machine that have access and share our medical records that will make decisions in terms of triage or sense of urgency related with medical treatment? It’s in ethical that a machine can make judgment about predicting future crimes or provide a credit risk score based on data that is related with our profiles?
Filed under: Artificial Intelligence, Cybernetics, Enterprise Architecture, Uncategorized Tagged: Artificial Intelligence, Cybernetics, Enterprise Architecture 
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