373 experts opinion: AGI / singularity by 2060 (2018 update)

373 experts opinion: AGI / singularity by 2060 (2018 update)

Artificial Intelligence scares and intrigues us. Almost ever week, there’s a new AI scare on the news like developers shutting down bots because they got too intelligent. Most of those news are a result of AI research misinterpreted by those outside of the field. Still, it shows the fear and interest in AI. And the greatest fear is singularity or Artificial General Intelligence, AI capable of improving itself and as a result reaching far beyond our capabilities. For those who came to get a quick answer:

  • Will singularity ever happen? According to most AI experts, yes.
  • When will it happen? Before the end of the century

For the more nuanced answer, please read it on. There have been several surveys of AI scientists asking about when such developments will take place.

Understand results of major surveys of AI researchers in 2 minutes

Source: Survey distributed to attendees of the Artificial General Intelligence 2009 (AGI-09) conference

In 2009, 21 AI experts participating in AGI-09 conference were surveyed. Experts believe AGI will occur around 2050, and plausibly sooner. You can see above their estimates regarding specific AI achievements: passing the Turing test, passing third grade, accomplishing Nobel worthy scientific breakthroughs and achieving superhuman intelligence.

In 2017 May, 352 AI experts who published at the 2015 NIPS and ICML conferences were surveyed. Based on survey results, experts estimate that there’s a 50% chance that AGI will occur until 2060. However, there’s significant difference of opinion based on geography: Asian respondents expect AGI in 30 years, whereas North Americans expect it in 74 years. Some significant job functions that are expected to be automated until 2030 are: Call center reps, truck driving, retail sales.

AI entrepreneurs are also making estimates on when we will reach singularity and they are a bit more optimistic than researchers:

  • Louis Rosenberg, computer scientist, entrepreneur and writer: 2030
  • Patrick Winston, MIT professor and director of the MIT Artificial Intelligence Laboratory from 1972 to 1997: 2040
  • Ray Kuzweil, computer scientist, entrepreneur and writer of 5 national best sellers including The Singularity Is Near : 2045
  • Jürgen Schmidhuber,  co-founder at AI company NNAISENSE and director of the Swiss AI lab IDSIA: ~2050

Understand why reaching AGI seems inevitable to most experts

These may seem like wild predictions, but they seem quite reasonable when you consider these facts:

  • Human intelligence is fixed unless we somehow merge our cognitive capabilities with machines like Elon Musk’s neural lace startup aims to do.
  • Machine intelligence depends on algorithms, processing power and memory. Processing power and memory have been growing at an exponential rate. As for algorithms, until now we have been good at supplying machines with necessary algorithms to use their processing power and memory effectively.

Considering that our intelligence is fixed and machine intelligence is growing, it is only a matter of time before machines surpass us unless there’s some hard limit to their intelligence. We haven’t encountered such a limit yet.

This is a good analogy for understanding exponential growth. While machines can seem dumb right now, they can grow quite smart, quite soon.

Illustratıon of exponential growth
Source: Mother Jones

Understand why some do not believe that we will ever reach AGI

There are 3 major arguments against the importance or existence of AGI[1]. We examined them along with their common rebuttals.

1- Intelligence is multi dimensional

Therefore AGI will simply be different not superior to human intelligence. This is true and human intelligence is also different than animal intelligence. Some animals are capable of amazing mental feats like squirrels remembering where they hid hundreds of nuts for months.

However, these differences do not stop humans from achieving far more than other species in terms of many typical measures of success for a species. For example humans are the species that contributes most to the bio-mass on the globe.

Different dimensions of intelligence
Source: Kevin Nelly

2- Intelligence is not the solution to all problems

For example, even the best machine analyzing existing data will probably not be able to find a cure for cancer. It will need to run experiments and analyze results to discover new knowledge in most areas.

This is true however intelligence can lead to better designed and managed experiments, enabling more discovery per experiment. History of research productivity should probably demonstrate this but data is quite noisy and there’s diminishing returns on research; we encounter harder problems like quantum physics as we solve simpler problems like Newtonian motion.

3- AGI is not possible because it is not possible to model the human brain

Theoretically it is possible to model any computational machine including the human brain with a relatively simple machine that can performs basic computations and has access to infinite memory and time. This is the Church-Turing hypothesis laid out in 1950. It is universally accepted however as stated, it requires certain difficult conditions: infinite time and memory.

Most computer scientists believe that it will take less than infinite time and memory to model the human brain. However, there is not a mathematically sound way to prove this belief as we do not understand the brain enough to understand its computational power. We will just have to build such a machine!

Hope this clarifies some of the major points regarding AGI. For more on how AI is changing the world, check out AI use cases on appliedAI.com


[1] Based partially on Wired’s summary of arguments against AGI and Wikipedia

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