Is AI the last invention humans will do?

I see this question popping up over and over again. At present it may look like Autonomous Machines will carry on the technological development and we sit and watch. Well – here is my thinking:

In 1980 the end of technology was predicted
I remember a day where my boss said “I think with the invention of the 8 bit microprocessor we are at the end of technology development – we will never see a 16 bit microprocessor in commercial use.” I was laughing but he was dead serious. Little did he know that we were not at the end but barely at the beginning of the micro computer revolution.

In 2020 the end of humanity will be seriously predicted
We are very much in the infant stage of AI. If we developed a fully autonomous and self aware AI system we are really at the beginning of a new technology era. Those machines will help us reach frontiers that even SciFi authors don’t see today but will fuel a whole new era of SciFi stories soon.

By 2030 We will see early tangible results
Imagine that we will be able to calculate the least possible effort to develop purified water for all humans on earth – and just do it. Be able to produce food for every single person even at 15 Billion population. We will quickly move away from plastic robots to fully biological material based robots.

By 2050 replacing general ‘work’ with AI Tax based income
By now we may need to / are in the luxurious position to replace 50 – 100 million jobs. By taxing Autonomous Machines we can fuel a pool of UBI (Unconditional Base Income) so those people will be covered and the ones how operate such machines can still do it profitably. Going forward most people in developed countries won’t have to find a job but can do what they are most excited about and evolve to “autonomous humans” in its own right.

By 2075 Smart material development may be in full swing
The very next big thing that already started is smart material and biological material. A Doctor in Germany developed the first artificial aortic ventricle of a heart made fully from biological material. This will keep going for at least 100 years. Smart material is changing its shape and even molecular structure based on electromagnetic impulses. Countless new applications.  The synthesis of smart material constructed and manipulated using – again – AI brings us to all new technological realms.

By 2100 We may reach a state of nearly abundant energy
We know that our sun is boosting unimaginable amount of energy every millisecond. Even our mother planet earth does that in its core. Today we still neither harvest that energy properly – let alone being able to emulate the phenomenon and create Terra Watts generated in a little box behind our homes.

By 2150 Body augmentation may get us to an age of 500 to 1,000 years
Then think about human body augmentation, Artificial yet biological “replacement parts” for virtually everything. Maybe not the brain by then but maybe even that.

By 2200 Terra-Forming
Again all new technologies, powerful energy generators, knowledge about space travel and planet construction. At that stage we actually need technology like AI to do a few billion iterations of possible ways to do what we want to do – a human being would never be able to do that. An AI system on the other side would never “create” the idea and suggesting:  “Hey human what do you think about the idea of making Mars an inhabitable planet”.

Between 2200 and 2500 longer distance space travel
We are not giving up on that one. And we cannot. Earth will be hit by a major asteroid in the next some 100,000 years and our human brain has further developed that we actually care. We will need to find ways to leave our paradise – one day.

Between 2,500 and 3,000 crossing parts of our galaxy
No, forget space ships and forget low speed travel of 100,000 miles per hour. It will be something entirely different – we still need to develop the very foundation of the necessary physics. By that time maybe we are able to develop our own chemical elements and the new Periodic Table is more like a book.

By 5,000 we may…
wonder what next and build a fully biological being, which only needs electric power to survive. We put it into a space ship and send it to Alpha Centaur, where it should start a life on its own – never letting it know where it came from, so we don’t get unexpected visits :) We just watch it develop from a safe distance. We may visit a bit closer – just hoping they don’t discover us and think we are a UFO with extra alpha centaurical live :)

So – NO, AI is not the last innovation it is actually the first of an all new technological, economical and societal era. We won’t hit a point with no more advancement any time soon. And IF, we will advance in a very different way and laugh about our neanderthal like toys including space ships, AI, terra forming and the other primitive gimmick.

Happy innovation

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Autonomous Machines – where are we today? Who may advance the most?

We came a long way in the last 1 and 1/2 years since this amazing video from Maurice Conti was recorded. Artificial Intelligence made huge progress. The hardware however is actually much behind the hopes. Autonomous machines like robots lack the skills to move like humans or animals. Other autonomous machines like cars or ships still lack the all encompassing sensor technology to be truly safe. Autonomous earth bound autonomous machines like chat bots and game computing however show great evolution in their hardware technology.

The software advances are more significant: AlphaGoZero was beating AlphaGo 100 to 0 – meaning the amazing AlphaGo program, which was beating the number one Go player in the world 4:1 was now beaten 100:0 by its next generation AM. The critical part of that story is that it was able to learn everything on its own. Chinese President Xi Jinpen announced his goal to be AI leader by 2030. German Economy & Science departments expressed their desire to make AI made in Germany a globally known quality brand for AI by 2030. Approximately 1.000 times as many regular people on the street became aware of a possible social shift in mankind. grander than anything we experienced or even imagined before. Fear however is spreading at almost alarming rate now – not a place we should be in. But it’s only indirectly the fear from machines. Deep inside our subconsciousness it is the fear of our own miss doing. Not our imperfection but doing things that are simply not right – and doing so in full awareness. Outside the technology and opportunity realm, we began to learn more from the AI development about ourselves than ever before.

How important is technology for AI?

In my work on that subject, I recently had an interesting thought. Mainly when I heard that the two vocal contender China and Germany longing for attention, I asked myself what they have to bring to the party. Today’s AI leader is clearly from California. But is technology really at the core of AI? Yes, we need powerful processors and lots of memory. But AI is no longer really about technology per see. At the core of any AI system are the algorithms, complex mathematical constructs that can describe a behavior, a process, and create results for possible more algorithms. Both Germans and Chinese are pretty good at that. Further more AI is equally dependent (today) on neural network skills. A structure where lots of data get feed in, and spill out results or even directives to other algorithms. Decision making procedures are other skills AI need to employ to create meaningful results. All these skills can be found widely in Germany and Switzerland.

Sooner or later all engineers will notice that no matter how much computing power they have it will never be enough. The game of GO is a great example. The number of possible moves from start to finish is said to exceed the number of atoms in the observable universe. Any AM (Autonomous Machine) will need to calculate its best result or step to a result based on the most probable right step, accepting it may not be the best. AMs need to be FAILURE TOLERANT. With that, an AI system actually gets closer to us humans. I’ve met AI researcher in Taiwan working especially on that part of the process.

But here comes – by far – the most challenging part of AI development that is actually useful for people: What questions do we have to have an AM answer it profoundly and efficient. To make AMs do repeatable jobs like in a production company, or repeatably answer questions, even millions of different questions, from customers in a pre-sales department, or answer questions from patience regarding their possible illness. that is not so complicated. But to answer the question: “How can we help politicians, make the right decisions that are in the interest of the population – and – taking long term effects into consideration?”. Most of us do not (yet) have a firm answer. Most of us, including me can’t even articulate that question comprehensive enough for any system or human to trigger the right solution finding process. Now that is an area where Central Europeans, including Germans are actually pretty good at – maybe better than others.

Artificial Intelligence is more about asking intelligent questions to get intelligent results that putting together fine technology.

While I can continue with a few more aspects of meaningful requirements for a great AM solution, it became very apparent to me that technology keeps taking less and less a center stage position and other, social, psychological, behavioral aspects move rapidly forward. It also daunted on my that there will probably not be a single country doing it all or being the leader – it is a global development where the most open minded and smartest people can jointly produce unprecedented results. Brut force leadership by order of a human leader is most certainly failing – even with 10 billion people. But some of them will contribute amazing solutions to the whole.

Leadership Framework

The World Innovations Forum put a leadership framework together to help all countries to get started and advance. Getting everybody involved makes a lot of sense when it comes to, what is said by some, the last innovation humans will do. Most importantly collaboratively developing and agreeing on a common set of rules will make this development much safer. But maybe we need an AI system to guide us through a process that may otherwise be too much driven by ego and self interest.

What’s next

The development of chat bots is evolving rapidly. From clunky little experiments a few years ago, we see great progress and probably have a highly sufficient “chat bot” by 2022 that is so strong and so versatile that it may replace more than 100 million call center employees with the only replacement of maybe a million people training and advancing those bots. By that time governments will have no other choice to tax the productivity of any AM no matter where those machines are hosted and no matter who owns them. The tax income then can be used to start the concept of a base income for those who won’t find work any soon. A whole taxation model will be available in the new book “World with no work“. By 2025 until 2028 we may be in a position that super advanced chat bots can replace many knowledge base systems including Medical Doctors, Lawyers, Bankers, Insurance Brokers, Inside sales people, cashiers and so forth. This may cause an even bigger avalanche of unemployment that my easily hit over half a billion people world wide. Only several million will be needed to review the medical suggestion, the investment advice etc. But will no longer need a time consuming deep dive. By 2030 robotics may have advance to be much more agile. My ultimate test for a robot would be: Successfully perform in three disciplines: 1) Successfully play soccer in one of the top leagues. 2) Climb Eiger North Face or any similar mountain and return safely to base camp. 3) Dance tango with one of the world class dancers (it takes two to tango). “It takes two to tango” has an inhered interesting aspect: unlike most dances, Tango is lead by both dancers with an unspoken intuition. That will kick start another avalanche of AMs performing tasks that have been conducted by well educated humans. With a constantly improved UBI (Unconditional Base Income) by now it becomes actually a desire to replace as many human jobs as possible and give humans the freedom to pick and chose activities they really love and be so good and social in it that there is no advantage to have robots. There is no advantage to mass produce robots that produce art better than humans can do. Art has no better or worst – Art is a human expression not a robotic mass produced expression, even if every piece would be individual.

Autonomous Humans

By 2040 or 2050, humans will rationalize that during the time of the industrialization, they lost their autonomy. No job – no happy live. If you can’t get into a company where somebody is telling you what to do, you won’t get the reward in cash that you need to survive. Or if you do not perform what is expected from you, you get fired. Not today – but in 100 years we will compare that life with modern slavery. How could it be that you – a free person – has only a few hours a day actually free. At least, unlike in the 1800’s you no longer get beaten up or cut off your hand, but still you call it yourself treadmill, you are very happy if it is 5 pm, you look forward to vacation, you have no or not enough time to do what you really would love to do, you may not even have your dream job, you can’t follow your intuition but the job rules and so forth.

However exactly that ‘YOU’, is the one who helped build a world that eventually transform to a much more liberal life, less dangerous tasks and way more pleasant. So nobody following the rules today is/was stupid. But look for the possible outcome in 30 years from now. Learn everything possible including risks and opportunities about AI and AM and only if you can make an educated decision, judge it – as an hopefully autonomous human.

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AI Leadership Framework For Countries

THIS IS WORK IN PROGRESS

Many countries explore ways to get not disconnected from the AI development even though the risks and opportunities of AI are highly controversial.

Since several of us are working in the Artificial Intelligence space for quite a while, we decided to put up an initial framework for country leaders. We believe that only a program developed in concert with other stakeholder has a good chance to be accepted by all.

It is in collaboration with our ambassadors in roughly 20 countries. More helping hands are very welcome. We will be updating this program on the go – leaving the previous versions as blog posts here. Theoretic AI is developing rather quickly and so should be this framework.

AI Leadership Framework

The “AI leadership framework” is a project in development. We are working with a large number of great minds from over 20 countries to postulate a framework that can be used as is, or as a base for a country’s own AI Leadership Strategy. While we see the risks that AI has, we see the grander opportunity for humanity. And if nothing at all, in the next 50 years we will learn more about ourselves than during the entire lifespan of humanity.

1) Data Awareness

Data is a new natural resource for the highly developed world. What was Gold, Coal, Oil, even healthy soil and so forth in the past,  is data in our immediate future. There is an abundance of data. The key is to intelligently harvest the overwhelming amount of available data. Being aware of the fact, that we all are creating new data, billions of data every single day, is the first step to create policies, infrastructure to protect – but also motivation to share those date. Like in previous technology developments, the US has been in a leadership position early on. Data power houses like Google, Amazon, Facebook, the credit card organizations and telecommunication companies, already sit on data like no other country.
Country leaders should understand: Data are generated in almost every country, including emerging countries and even some sub emerging countries. Not being able to use those data in a secure and privacy protected way is a major obstacle in a countries development. Natural resources just got an additional position in their list.

2) Access to data

The more data can be assessed the better the results from AI systems. In particular in the early days of any AI development, it is critical to get access to an enormous amount of data. Enormous means several hundred thousand records about the same topic. Over regulated and fearful societies and those with fear driven privacy campaigns are clearly in a disadvantages position. Amazon has access to trillions of dollars worth of shopping from past years. Together with data usage from their AWS business unit Amazon is one of the top player globally. Google sits on quadrillion of data points from all the searches and knows what people look for, why, what problems they have, what products they search,what illness they have and so forth. Facebook, unlike the other two has much more social interaction related data. The recent collaboration with credit card institutions provide Facebook a hot mix of social and commercial data and relations. Of course privacy is an issue but not using the data is like having hectares of apple trees but letting the apples rotten in the ground.
Country leaders should recognize that blocking data access due to the inability to protect the owner’s privacy of those data brings those countries behind. Retraining a population that ‘it is OK now’ is a daunting task.

3) Engineering

AI is no longer an IT discipline. AI requires top level mathematical knowledge, understanding of neural networks, understanding of reasoning and decision making processes, understanding in cognitive behavior, awareness know how, and much more. Image and speech recognition skills are simply a given. The vast majority looks at AI as a software code that is written by humans and can do at best as well as the programmer. That an AI system can not only perform computational processes but also build intelligent correlations, make then decisions and outperform humans in almost every predictable project is foreign to most of the postulation. The algorithms (mathematical procedures) allow AI systems to learn from hundreds of thousands of situations, then construct millions of situations similar to those they learned from and have a richer set of “experience” than any human ever being able to accumulate. While this is good – we need to understand the implications.
Country leaders should know that no longer only engineers are needed to develop leading AI applications but also Social Scientists,  Biologists, Mathematician, human behavior experts and related skills.

4) General Education

In past major development shifts, the education of what’s happening was more or less based on the effort of the businesses who produced and marketed those new technologies. However the possible impact is too significant to only hope the education will work out. If 50% of jobs will be irreplaceable eliminated, we need concepts and education how who this will not turn out as a catastrophe. We need to explore options in advance and educate those who have been educated to look for work and do what others tell them to do. what opportunities are out there in this new world. For the past 300,000 years humans have been taking care of themselves, have been rather autonomous and been creative to survive. In the past 200 years that has changed. The main job was to look for work and just do it. We are in a way going back to more autonomy and self determination. While this is an amazing and positive development, for many people it is on open void they may not be able to fill by themselves. Education and guidance is a key aspect of leadership – always was.
Country leader should seriously consider a greater makeover in their respective education systems. Mechanical learning of Physics, Math, Chemistry, Biology, History, Languages, is no longer enough. And as our knowledge base now doubles every year and the learning capacity of the young already crossed the limits, we need to consider actually reducing the amount of the content in the core classes and add data technology, society and political rights and responsibilities as these topics require a better understanding of everybody.

5) Language Empowerment

The world’s information is by and large stored in English language. Even the use of the term ‘Artificial Intelligence’ is important to be held in English and not in a local language. One of the key success aspects of AI is the openness and willingness to cooperate globally – that means by default in English. Leadership by ‘closed shop’, and keeping everything close to ones chest and secretive will never lead to superiority.
Country leaders should seriously consider reviewing the language learning in each country. Even though it is part of the general education, it has a very special position in the AI development. No longer it is only about the globally universal language of code writing, there is also the new language of system interaction. Already today AI components outperform any language on earth with more than 1 to 100 relative to English. Roughly 200 French Language ‘Skills” (applications) or close to 3,000 German skills versus more than 10,000 English skills.

6) Culture & Failure Tolerance

Whatever a team is creating, it is critical to get the early prototype rapidly into the market and work with massive amounts of actions. AI cannot be only tested in a lab – it needs to be tested in the market. The European or Asian perfectionism is counterproductive to AI development and will automatically make those actors fall behind. Google’s AI project that was used to learn about battery usage in Android smart phones moved within six months from concept to being used globally. We can learn only from errors. We will not learn from a perfectly working solutions. What sounds stupid to many engineers has been proven right over and over again. The motto Fail and fail fast is even more important in AI development.
Country leaders may want to consider driving an initiative that makes making mistakes an act of learning and progress rather than an act of failing. Chinese president Xi Jinping addressed Chinese entrepreneurs early 2018: ‘Making mistakes is the best way to learn fast’.

7) Transparency

Due to the competitive nature of any new technology, we most likely will never be able to find out who is working on what. Our brains are still the most private part of our lives – and hopefully will be forever. Yet, we should develop a work ethic that calls for voluntary transparency on the Matter of AI development. Now, recent incidents demonstrated that a business may not trust its own government because of its sheer power. A government should not even attempt to play a controlling role in the transparency question. And since trust is one of the key issues in that, maybe a system like we know from the blockchain development maybe a future option. Another reason why we should keep governments out of this role is the lack of trust among governments themselves. The current suggestion is that AI scientists select a consortium of trusted, anonymous third parties who get tasked to oversee the development as such and analyses the potential risks – with no authority power.
Country leaders may want to consider endorsing such an engagement, maybe send an observer but not ‘control’ it in any aspect. The control should instead lay in relevant and meaningful AI safety policies and law enforcement activities.

8) Taxation

There is a good potential that Autonomous Machines (AI driven systems) could wipe out 50% of the ordinary jobs by 2100 (plus/minus 50 years). Any given society would not recover from such a situation without well thought out planning. One concept maybe that each robot may be charged with a tax equal to one employee. That “AM-Tax” can then be used to fill a fund for unconditional base income or similar system. While the company would still have to purchase such a machine, it can quickly amortize the investment with this artificial employee not taking vacation, not needing social extras and possibly can simply rented as needed. Several scenarios can be found in “World with no work”.
Country leaders should be way ahead of time working on models for their respective society. That includes considering the competition from outside their country. The AM-Tax might be on conjunction with the production output (revenue) or operative savings (cost) they produce or save.

9) AI / AM imports

When importing AI from other countries we need to be aware that this may inherit a certain danger. Those machines may not comply with a country’s Safety & Privacy roles. Data maybe abused or used illegally and more. Importing such machines is a similar subject like importing weapons.
Country leaders should consider to establish early on AM (Autonomous Machine) Import rules and most importantly taxes in line with their overall AI or AM taxation.

10) Safety & Privacy Policies

Another key aspect of the leadership framework is the existence of the “Safety Trio”:
1) Privacy & Data Policies
2) Criminal Acts Policy
3) Human Protection Policies

10.1) Privacy & Data policies
need to be established to not only protect the general population from misuse of data but also education about the consequences of not providing data. Data as such needs to be structured beyond the act of privacy protection but also the protection of data, that belong to the creator of those data. Yet, it needs to be understood that data can either belong to one person or legal entity in its entirety or belong to a whole group pf people or entities. The complexity and permutation of data needs to be carefully explored on the go.

10.2) Criminal Acts Policy
Most likely the act of hacking systems and stealing data, corrupting data or systems or destroying either data, systems or network infrastructure will want to be set as a serious criminal act. As systems get more sophisticated they also can cause more damage than in the past and can bring people and a whole country into serious trouble. AI leadership needs to demonstrate its sensitivity for protection while at the same time its openness for sharing data. As such, hacking needs to be elevated to a serious criminal act with substantial penalties. The criminals act policy should also expanded into political treaties where country leaders agree on respecting the criminal acts policies of each other.

10.3) Human Protection Policy
There is s great level of fear, that AI based Robots, so called autonomous machines, may be at risk of harming humans. Right or wrong, AI leadership requires responsiveness and offers a solution. A possible method is to legally enforce that every autonomous machine will need to have a mechanism to be remotely shut off by especially selected authorities and/or mechanisms. A structure like the domain name service where systems are distributed around the globe may also be applicable to distribute the shut of mechanism. Robots without such a mechanism maybe considered illegal and by order of the law destroyed and the creator and owner penalized. The instantiation of the ‘Criminal Acts Policy’ is in particular important for this ‘Human Protection Policy’.

 

 

SUMMARY

As stated in the beginning, the AI Leadership Framework is in an early stage and far from being complete. But in the interest of transparency also of our work, we wanted to share where we are at this stage and what we are working on. Suggestions may change into very different directions based on inputs and the work we are doing going forward.

 

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