Whiplash: How to Survive Our Faster Future

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Survey respondents were given the following definition of human-level machine intelligence: “Human-level machine intelligence (HLMI) is reached when machines are collectively able to perform almost all tasks (>90% of all tasks) that are economically relevant better than the median human paid to do that task in 2019. You should ignore tasks that are legally or culturally restricted to humans, such as serving on a jury.” It could be telling us something is missing from what we think is our standard model," says Freedman. "We don't yet know the reason why this is happening, but it's an opportunity for a discovery." The impact of clouds on global temperature is a complex area of research that scientists have been working on for decades.

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Over a century since Hubble's first estimate for the rate of cosmic expansion, that number has been revised downwards time and time again. Today's estimates put it at somewhere between 67 and 74km/s/Mpc (42-46 miles/s/Mpc). LabCorp, a clinical laboratory organization, has teamed up with healthtech company Ciox Healthto collaborate on the use of AI to learn why COVID-19 affects individuals in different ways. Their collaboration leverages machine learning and natural language processing to make sense of the unstructured information contained in medical records. The information is then analyzed to help predict an individual’s susceptibility to the virus. By mid-April LabCorp had completed 650,000 COVID-19 tests. Prior to that, few people were tested until they were incapacitated. Delivery services Bryce Goodman is Chief Strategist for Artificial Intelligence and Machine Learning at the Department of Defense’s Innovation Unit, where he oversees a range of large-scale projects including the implementation of AI for humanitarian assistance and disaster response, predictive maintenance, counter-disinformation, predictive health, and supply chain optimization. Her research was announced in various places, including the AI Alignment Forum: Ajeya Cotra (2020) – Draft report on AI timelines. As far as I know the report itself always remained a ‘draft report’ and was published here on Google Docs (it is not uncommon in the field of AI research that articles get published in non-standard ways). In 2022 Ajeya Cotra published a Two-year update on my personal AI timelines. Other studies

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Survey respondents were asked the following: “These questions will ask your opinion of future AI progress with regard to human tasks. We define human tasks as all unique tasks that humans are currently paid to do. We consider human tasks as different from jobs in that an algorithm may be able to replace humans at some portion of tasks a job requires while not being able to replace humans for all of the job requirements. For example, an AI system(s) may not replace a lawyer entirely but may be able to accomplish 50% of the tasks a lawyer typically performs. In how many years do you expect AI systems to collectively be able to accomplish 99% of human tasks at or above the level of a typical human? Think feasibility.” As highlighted in the annotations, half of the experts gave a date before 2061, and 90% gave a date within the next 100 years. The tactical (and strategic) leaders who embrace the character of incentive aligners will be much more effective than those who rely on traditional discipline." COVID-19 has increased the gap between the digital leaders and the digital laggards…We’ve had 3 years of digital cultural transformation in 3 months.” — Paul Daugherty , Accenture

Faster Future 2.0

At the same time, there is large agreement in the overall picture. The timelines of many experts are shorter than a century, and many have timelines that are substantially shorter than that. The majority of those who study this question believe that there is a 50% chance that transformative AI systems will be developed within the next 50 years. In this case it would plausibly be the biggest transformation in the lifetime of our children, or even in our own lifetime. For example, the “lifetime anchor” hypothesis estimates the total computation performed by the human brain up to age ~32. Include anecdotes and other personal or professional experiences that help in making the SOP even more interesting.In Issac Asimov’s Foundation series, humanity can travel from planet to planet, star to star or across the universe using jump drives. As a kid, I read as many of those stories as I could get my hands on. I am now a theoretical physicist and study nanotechnology, but I am still fascinated by the ways humanity could one day travel in space. In addition to this framing effect, there is a larger effect driven by how the concept of HLMI is defined. We can see this in the results from the previous edition of this survey (the result from the 2022 survey hasn’t yet been published). For respondents who were given the HLMI definition above, the average forecast for a 50% chance of HLMI was 2061. A small subset of respondents was instead given another, logically similar question that asked about the full automation of labor; their average forecast for a 50% probability was 2138, a full 77 years later than the first group. Another example is Ernest Rutherford, father of nuclear physics, calling the possibility of harnessing nuclear energy "moonshine." The research paper by John Jenkin discusses why. John G. Jenkin (2011) – Atomic Energy is ‘‘Moonshine’’: What did Rutherford Really Mean?. Published in Physics in Perspective. DOI 10.1007/s00016-010-0038-1 Faster than light travel is the only way humans could ever get to other stars in a reasonable amount of time.

Future batteries, coming soon: Charge in seconds, last months Future batteries, coming soon: Charge in seconds, last months

Michael Connolly blends leading technology, innovation and education to help companies grow faster. Recently he was the Executive Vice President for Global Sales at Singularity University, the eminent global pioneer in preparing enterprise executives and entrepreneurs for the future, through understanding and applying exponential technologies.Other surveys of AI experts come to similar conclusions. In the following visualization, I have added the timelines from two earlier surveys conducted in 2018 and 2019. It is helpful to look at different surveys, as they differ in how they asked the question and how they defined human-level AI. You can find more details about these studies at the end of this text. The visualization shows the forecasts of 1128 people – 812 individual AI experts, the aggregated estimates of 315 forecasters from the Metaculus platform, and the findings of the detailed study by Ajeya Cotra. If you’re basing your strategy on pre-pandemic, traditional business models You need to fire your old framework.We can be sure that the disruptive COVID-19 crisis has permanently transformed our world.We cannot be sure which of the trends we discussed are temporary, and which mark the beginning of the end for certain industries and business models.

Cooling effect of clouds ‘underestimated’ by climate models

I hope my credibility has the power to impress you and earn me a seat at your prestigious university. As in Grace et al 2022, each survey respondent was randomly assigned to give their forecasts under one of two different framings: “fixed-probability” and “fixed-years.” As was found before, the fixed-years framing resulted in longer timelines on average: the year 2070 for a 50% chance of HLMI, compared to 2050 under the fixed-probability framing. The study by Gruetzemacher et al. published in 2019 It would be able to choose actions that allow the machine to achieve its goals and then carry out those actions. It would be able to do the work of a translator, a doctor, an illustrator, a teacher, a therapist, a driver, or the work of an investor. We show the results using this definition of AI in the chart, as we judged this definition to be most comparable to the other studies included in the chart. Silanano is a battery tech startup that's bringing this technique to market and has seen big investment from companies like Daimler and BMW. The company say that its solution can be dropped into existing lithium-ion battery manufacturing, so it's set for scalable deployment, promising 20 per cent battery performance boost now, or 40 per cent in the near future.What I do take away from these surveys however, is that the majority of AI experts take the prospect of very powerful AI technology seriously. It is not the case that AI researchers dismiss extremely powerful AI as mere fantasy. The following questions ask about ‘high-level machine intelligence’ (HLMI). Say we have ‘high-level machine intelligence’ when unaided machines can accomplish every task better and more cheaply than human workers. Ignore aspects of tasks for which being a human is intrinsically advantageous, e.g., being accepted as a jury member. Think feasibility, not adoption. For the purposes of this question, assume that human scientific activity continues without major negative disruption.”