AI is coming ahead of schedule: are we facing a “rebellion of the machines” in the near future?

Increasingly, news headlines scare people with the imminent replacement of employees with robots, but is this really so? At what stage is the development of artificial intelligence now and is it worth it to be afraid of the “rise of the machines”? Aleksey Sukhodoev, a representative of the board of the international social and financial platform Sky World Community, an expert in international business development, strategist and visionary, told how things are and what you need to pay attention to in order to prepare your business for the emergence of artificial intelligence (AI).

Rodney Brooks, a roboticist at the Massachusetts Institute of Technology and co-founder of iRobot, predicts the emergence of artificial intelligence no earlier than 2300: “Now is a difficult time to understand the true promise and dangers of AI. Most of what we read in the headlines… I think is completely untrue”.

However, many scientists and researchers argue that there is at least a chance that human-level artificial intelligence could be achieved in the next decade. Back in 2017, University of Alberta computer science professor Richard Sutton stated that “the development of AI to the human level is quite possible by 2030 (25%) or 2040 (50%)”.

What determines the rate of emergence of artificial intelligence?

There are three types of artificial intelligence: weak (which we are now), strong (or general artificial intelligence - AGI) and super-AI (this is just the stage when a machine is smarter than a person). To move from weak AI to strong AI, a person needs to fully understand their brain and its properties in order to transfer them to a computer, and at least this will take a lot of time. The super-AI stage is what we see in science fiction films: when a computer learns not only to use all the possibilities of the human mind loaded into it, but also to learn by itself, finding bugs and fixing them.

The most respected researchers and academics claim that we are decades away from realizing AGI, and some even predict that we won't see AGI this century.

If all this is still so far away, then why worry about it and somehow prepare for the emergence of AI now?

Even the small likelihood of achieving AGI in the next decade justifies attention to developments in this area, given the potentially dramatic tipping point that AGI could cause in society. It is better to start preparing your business and your usual life now for what in a couple of decades may become commonplace.

What can accelerate the development of AI and what achievements affect it?

First, the main algorithmic achievements and new approaches to robotics.

One of the concepts that is currently being actively explored is the concept of embodied cognition. The concept's hypothesis is that robots will need to learn from their environment through multiple senses, as humans do in the early stages of life, and that they will have to experience the physical world through a human-like body in order to develop cognitively in the same way as people.

As Gary Markus and Ernest Davis point out in their book AI Reboot, “We believe that real progress in AI will begin with understanding what kinds of knowledge and beliefs need to be built in before learning to enable everything else.” The recent success of deep learning may have diverted researchers' attention from the more fundamental cognitive work needed to make progress in AGI.

Secondly, the achievements of computer technology. The use of GPUs for training deep neural networks has been an important step forward, enabling the major advances of the past few years. GPUs uniquely allowed the complex computations required by Hinton's backpropagation algorithm to be performed in parallel, allowing extremely complex neural networks to be trained in a short time. And before any further exponential growth in the direction of AGI can be expected, a similar inflection point in computing infrastructure must be matched with unique algorithmic advances.

One of the most likely inflection points may be quantum computing, which is used to solve very complex statistical problems that modern computing power cannot handle. However, since it wasn’t until late 2019 that the first real evidence emerged that quantum computers could handle such tasks, the hardware and software to solve the problems needed to advance AI might not arrive until 2035 at the earliest.

Thirdly, a significant increase in the volume of data, and from new sources. New approaches to robotics can provide new sources of training data. By placing even basic humanoid robots among humans — and doing so at scale — large datasets that mimic our own senses could help close the learning feedback loop that advances the state of the art.

What do you, as leaders, do with all this information? How to prepare your business and team?

Be aware . Follow developments in AI, watch startups, find analysts, or develop your own analytics system to track development progress.

Adapt your environment. Do not wait until strong AI is created, implement narrow developments in your company now. These include simplifying processes, structuring physical spaces, and transforming analog systems and unstructured data into digital systems and structured data. Modern digital and automation programs can ease the transition to AGI for your customers, employees, and stakeholders.

Invest. Combined human-machine interfaces or man-in-the-loop technologies that enhance human intelligence rather than replace it. This category includes everything from analytics to improve people's decision making to cognitive agents that work alongside call center agents. The use of technology to increase human productivity has been the engine of economic progress and is likely to remain so for the foreseeable future.

Organize your employees. The rigid organizational structures and operating models of the past are ill-suited to a world in which AI is rapidly evolving. Accept people's ability to work in challenging environments and self-organize.

Bet small to secure strategic opportunities in the areas of your business most affected by AGI change. For example, consider investing in technology firms with ambitious AI R&D projects in your industry. There is no way to know when (or if) your bets will pay off, but targeted investments today can help you hedge against existential risks your business may face in the future.