Was the industrial revolution a drastic departure from historic trends?

*Updated Nov 18, 2020*

We do not have a considered view on this topic.

Details
-------

We have not investigated this topic. This is an incomplete list of evidence that we know of:

* David Roodman’s analysis of the surprisingness of the industrial revolution under his 2020 model of economic history.[1](https://aiimpacts.org/was-the-industrial-revolution-a-drastic-departure-from-historic-trends/#easy-footnote-bottom-1-2760 "Open Philanthropy. “Modeling the Human Trajectory,” June 15, 2020. https://www.openphilanthropy.org/blog/modeling-human-trajectory.")
* Ben Garfinkel’s analysis of whether economic history suggests a singularity[2](https://aiimpacts.org/was-the-industrial-revolution-a-drastic-departure-from-historic-trends/#easy-footnote-bottom-2-2760 "“Does Economic History Point Toward a Singularity? – EA Forum.” Accessed November 17, 2020. https://forum.effectivealtruism.org/posts/CWFn9qAKsRibpCGq8/does-economic-history-point-toward-a-singularity.")
* Robin Hanson’s analysis of historic economic growth understood as a sequence of exponential modes.[3](https://aiimpacts.org/was-the-industrial-revolution-a-drastic-departure-from-historic-trends/#easy-footnote-bottom-3-2760 "Hanson, Robin. “Long-Term Growth As A Sequence of Exponential Modes,” 2000, 24.")
* On a [log(GWP)-log(doubling time) graph](https://aiimpacts.org/historical-growth-trends/), the industrial revolution appears to be almost perfectly on trend, according to our very crude analysis.

### Relevance

The nature of the industrial revolution is relevant to AI forecasting in the following ways:

* If growth during the industrial revolution is a highly improbable aberration from longer term trends, it suggests that it is a consequence of specific developments at the time, most saliently new technologies. This suggests that new technologies can sometimes alone cause changes at the level of the global economy.
* ‘The impact of the industrial revolution’ is sometimes used as a measure against which to compare consequences of AI developments. Thinking here may be sharpened by clarification on the nature of the industrial revolution. This use is likely related to the point above, where ‘the scale of the industrial revolution’ is taken to be a historically plausible scale of impact for the most ambitious technologies.
* If economic history is best understood as a sequence of ‘growth modes’, per Hanson 2000,[4](https://aiimpacts.org/was-the-industrial-revolution-a-drastic-departure-from-historic-trends/#easy-footnote-bottom-4-2760 "Hanson, Robin. “Long-Term Growth As A Sequence of Exponential Modes,” 2000, 24.") the industrial revolution being one, this changes our best extrapolation to the future. For instance, we might expect the continuation of the current mode to be slower than in a continuously super-exponential model, but may also expect to meet a new growth mode at some point, which may be substantially faster (and have other characteristics recognizable from past ‘growth mode’ changes). See Hanson 2000 for more on this.

Notes
-----


Energy efficiency of MacCready Gossamer Albatross

*Updated Nov 9, 2020*

The MacCready *Gossamer Albatross*:

* covered around 2.0—4.6 m/kJ
* and moved mass at around 0.1882 —0.4577 kg⋅m/J

Details
-------

The **MacCready *Gossamer Albatross*** was a human-powered flying machine that crossed the English Channel in 1979.[1](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-1-2756 "“The Gossamer Albatross is a human-powered aircraft built by American aeronautical engineer Dr. Paul B. MacCready‘s company AeroVironment. On June 12, 1979, it completed a successful crossing of the English Channel to win the second £100,000 (£509644 today) Kremer prize.[1]“

“MacCready Gossamer Albatross.” In Wikipedia, October 7, 2020. https://en.wikipedia.org/w/index.php?title=MacCready_Gossamer_Albatross&oldid=982283381.") The pilot pedaled the craft, seemingly as if on a bicycle. It had a gross mass of 100kg, flying across the channel,[2](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-2-2756 "“The empty mass of the structure was only 71 lb (32 kg), although the gross mass for the Channel flight was almost 220 lb (100 kg). “

“MacCready Gossamer Albatross.” In Wikipedia, October 7, 2020. https://en.wikipedia.org/w/index.php?title=MacCready_Gossamer_Albatross&oldid=982283381.") and flew 35.7 km in 2 hours and 49 minutes.[3](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-3-2756 "“Allen completed the 22.2 mi (35.7 km) crossing in 2 hours and 49 minutes, achieving a top speed of 18 mph (29 km/h) and an average altitude of 5 ft (1.5 m).”

“MacCready Gossamer Albatross.” In Wikipedia, October 7, 2020. https://en.wikipedia.org/w/index.php?title=MacCready_Gossamer_Albatross&oldid=982283381.") The crossing was difficult however, so it seems plausible that the *Gossamer Albatross* could fly more efficiently in better conditions.

We do not know the pilot’s average power output, however:

* Wikipedia claims at least 300W was required to fly the craft[4](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-4-2756 "“To maintain the craft in the air, it was designed with very long, tapering wings (high aspect ratio), like those of a glider, allowing the flight to be undertaken with a minimum of power. In still air, the required power was on the order of 300 W (0.40 hp), though even mild turbulence made this figure rise rapidly.[2]“

“MacCready Gossamer Albatross.” In Wikipedia, October 7, 2020. https://en.wikipedia.org/w/index.php?title=MacCready_Gossamer_Albatross&oldid=982283381.")
* Chung 2006, an engineering textbook, claims that the driver, a cyclist, could produce around 200W of power.[5](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-5-2756 "Chung, Yip-Wah. Introduction to Materials Science and Engineering. CRC Press, 2006. p89")
* Our impression is that 200W is a common power output over houres for amateur cycling. For instance, one of our researchers is able to achieve this for three hours.[6](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-6-2756 "https://www.strava.com/activities/272615649/overview")

The best documented human cycling wattage that we could easily find is from professional rider Giulio Ciccone who won a stage of the Tour de France, then uploaded power data to the fitness tracking site Strava.[7](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-7-2756 "Strava. “Yellow Jersey – Giulio Ciccone’s 158.8 Km Bike Ride.” Accessed November 9, 2020. https://www.strava.com/activities/2525139293.") His performance suggests around 318W is a reasonable upper bound, supposing that the pilot of the *Gossamer Albatross* would have had lower performance.[8](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-8-2756 "For an upper value, we used a combination of two metrics given on the website. The first metric is his “weighted average power” for the Tour de France stage, which was 318W. Weighted average power is a way of averaging power over a ride with highly variable power which gives higher weight to higher power portions of the ride, and is used by athletes and coaches to estimate the maximum power that a rider could sustain for a long time, if they had a steady power output. The second metric is Ciccone’s maximum power from his Tour race applied over the duration of the MacCready flight (2 hours and 40 min) which is 5W/kg body weight. For the pilot, Allen, riding with the same power per body weight (65 kg), this would be equivalent to 322W, a similar value to his weighted average power. We use the lower of the two values, 318W.")
To find the energy used by the cyclist, we divided power output by typical efficiency for a human on a bicycle, which according to Wikipedia ranges from .18 to .26.[9](https://aiimpacts.org/maccready-gossamer-albatross/#easy-footnote-bottom-9-2756 "“The required food can also be calculated by dividing the output power by the muscle efficiency. This is 18–26%. “

“Bicycle Performance.” In Wikipedia, October 9, 2020. https://en.wikipedia.org/w/index.php?title=Bicycle_performance&oldid=982652996.")
### Distance per Joule

For distance per energy this gives us a highest measure of:

35.7 km / ((200W \* (2 hours + 49 minutes))/0.26) = 4,577 m/MJ

And a lowest measure of:

35.7 km / ((318W \* (2 hours + 49 minutes))/0.18) = 1,993 m/MJ

### Mass per Joule

For weight times distance per energy this gives us a highest measure of:

(100kg \* 35.7 km) / ((200W \* (2 hours + 49 minutes))/0.26) = 0.4577 kg⋅m/j

And a lowest measure of:

(100kg \* 35.7 km) / ((318W \* (2 hours + 49 minutes))/0.17) =  0.1882 kg⋅m/j

*Primary author: Ronny Fernandez*

Notes
-----


Energy efficiency of Boeing 747-400

*Updated Nov 5, 2020*

The Boeing 747-400:

* covers around 0.0021m/kJ.
* and moves mass at around 0.39 – 0.83 kg.m/J

Details
-------

The *Boeing 747-400* is a 1987 passenger plane.[1](https://aiimpacts.org/energy-efficiency-of-boeing-747-400/#easy-footnote-bottom-1-2745 "“The Boeing 747-400 is a wide-body airliner produced by Boeing Commercial Airplanes, an advanced variant of the initial Boeing 747. The “Advanced Series 300” was announced at the September 1984 Farnborough Airshow, targeting a 10% cost reduction with more efficient engines and 1,000 nmi (1,850 km) more range. ”

“Boeing 747-400.” In Wikipedia, November 2, 2020. https://en.wikipedia.org/w/index.php?title=Boeing_747-400&oldid=986725646.")
### Distance per Joule

The plane uses 10.77 kg/km of fuel on a medium haul flight.[2](https://aiimpacts.org/energy-efficiency-of-boeing-747-400/#easy-footnote-bottom-2-2745 "“Fuel Economy in Aircraft.” In Wikipedia, October 22, 2020. https://en.wikipedia.org/w/index.php?title=Fuel_economy_in_aircraft&oldid=984919809.") We do not know what type of fuel it uses, but typical values for aviation fuel are around 44MJ/kg.[3](https://aiimpacts.org/energy-efficiency-of-boeing-747-400/#easy-footnote-bottom-3-2745 "“The net energy content for aviation fuels depends on their composition. Some typical values are:[15]

BP Avgas 80, 44.65 MJ/kg, density at 15 °C is 690 kg/m3 (30.81 MJ/litre).

Kerosene type BP Jet A-1, 43.15 MJ/kg, density at 15 °C is 804 kg/m3 (34.69 MJ/litre).

Kerosene type BP Jet TS-1 (for lower temperatures), 43.2 MJ/kg, density at 15 °C is 787 kg/m3 (34.00 MJ/litre).”

“Aviation Fuel.” In Wikipedia, September 13, 2020. https://en.wikipedia.org/w/index.php?title=Aviation_fuel&oldid=978262126.") Thus to fly a kilometer, the plane needs 10.77 kg of fuel, which is 10.77 x 44 MJ = 474 MJ of fuel. This gives us 0.0021m/kJ.

### Mass.distance per Joule

According to Wikipedia, the 747’s ‘operating empty weight’ is 183,523 kg and its ‘maximum take-off weight’ is 396,893 kg.[4](https://aiimpacts.org/energy-efficiency-of-boeing-747-400/#easy-footnote-bottom-4-2745 "“Boeing 747-400.” In Wikipedia, November 2, 2020. https://en.wikipedia.org/w/index.php?title=Boeing_747-400&oldid=986725646.") We use the range 183,523 kg—396,893 kg since we do not know at what weight in that range the relevant speeds were measured.

We have:

* Distance per kilojoule: 0.0021m/kJ
* Mass: 183,523 kg—396,893 kg

This gives us a range of 0.39 – 0.83 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----

Energy efficiency of Boeing 747-400


Energy efficiency of Airbus A320

*Updated Nov 5, 2020*

The Airbus A320:

* covers around 0.0078 m/kJ
* and moves mass at around 0.33 – 0.61 kg.m/J

Details
-------

The *Airbus A320* is a 1987 passenger plane.[1](https://aiimpacts.org/energy-efficiency-of-airbus-a320/#easy-footnote-bottom-1-2743 "“The Airbus A320 family are narrow-body airliners designed and produced by Airbus. The A320 was launched in March 1984, first flew on 22 February 1987, and was introduced in April 1988 by Air France.”

“Airbus A320 Family.” In Wikipedia, October 30, 2020. https://en.wikipedia.org/w/index.php?title=Airbus_A320_family&oldid=986182483.")
### Distance per Joule

The plane uses 2.91 kg of fuel per km on a medium haul flight.[2](https://aiimpacts.org/energy-efficiency-of-airbus-a320/#easy-footnote-bottom-2-2743 "“Fuel Economy in Aircraft.” In Wikipedia, October 22, 2020. https://en.wikipedia.org/w/index.php?title=Fuel_economy_in_aircraft&oldid=984919809.") We do not know what type of fuel it uses, but typical values for aviation fuel are around 44MJ/kg.[3](https://aiimpacts.org/energy-efficiency-of-airbus-a320/#easy-footnote-bottom-3-2743 "“The net energy content for aviation fuels depends on their composition. Some typical values are:[15]

BP Avgas 80, 44.65 MJ/kg, density at 15 °C is 690 kg/m3 (30.81 MJ/litre).

Kerosene type BP Jet A-1, 43.15 MJ/kg, density at 15 °C is 804 kg/m3 (34.69 MJ/litre).

Kerosene type BP Jet TS-1 (for lower temperatures), 43.2 MJ/kg, density at 15 °C is 787 kg/m3 (34.00 MJ/litre).”

“Aviation Fuel.” In Wikipedia, September 13, 2020. https://en.wikipedia.org/w/index.php?title=Aviation_fuel&oldid=978262126.") Thus to fly a kilometer, the plane needs 2.91kg of fuel, which is 2.91 x 44 MJ = 128MJ of fuel. This gives us 0.0078 m/kJ

### Mass.distance per Joule

According to modernairliners.com, the A320’s ‘operating empty weight’ is 42,600 kg and its ‘maximum take-off weight’ is 78,000 kg.[4](https://aiimpacts.org/energy-efficiency-of-airbus-a320/#easy-footnote-bottom-4-2743 "“Airbus A320 Specs – Modern Airliners.” Accessed November 5, 2020. https://modernairliners.com/airbus-a320-introduction/airbus-a320-specs/.") We use the range 42,600—78,000 kg, since we do not know at what weight in that range the relevant speeds were measured.

We have:

* Distance per kilojoule: 0.0078 m/kJ
* Mass: 42,600—78,000 kg

This gives us a range of 0.33 – 0.61 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----

Energy efficiency of Airbus A320


Energy efficiency of North American P-51 Mustang

*Updated Nov 5, 2020*

The North American P-51 Mustang:

* flew around 0.073—0.092 m/kJ
* and moved mass at around 0.25 – 0.50 kg.m/J

Details
-------

The *North American P-51 Mustang* was a 1940 US WWII fighter and fighter-bomber.[1](https://aiimpacts.org/energy-efficiency-of-north-american-p-51-mustang/#easy-footnote-bottom-1-2737 "The North American Aviation P-51 Mustang is an American long-range, single-seat fighter and fighter-bomber used during World War II and the Korean War, among other conflicts. The Mustang was designed in April 1940 by a design team headed by James Kindelberger[6] of North American Aviation (NAA) in response to a requirement of the British Purchasing Commission.”

“North American P-51 Mustang.” In Wikipedia, October 19, 2020. https://en.wikipedia.org/w/index.php?title=North_American_P-51_Mustang&oldid=984347874.")
### Mass

According to Wikipedia[2](https://aiimpacts.org/energy-efficiency-of-north-american-p-51-mustang/#easy-footnote-bottom-2-2737 "“North American P-51 Mustang.” In Wikipedia, October 19, 2020. https://en.wikipedia.org/w/index.php?title=North_American_P-51_Mustang&oldid=984347874."):

* **Empty weight:** 7,635 lb (3,465 kg)
* **Gross weight:** 9,200 lb (4,175 kg)
* **Max takeoff weight:** 12,100 lb (5,488 kg)

We use the range 3,465—5,488 kg, since we do not know at what weight in that range the relevant speeds were measured.

### Distance per Joule

Wikipedia tells us that cruising speed was 362 mph (162 m/s)[3](https://aiimpacts.org/energy-efficiency-of-north-american-p-51-mustang/#easy-footnote-bottom-3-2737 "“North American P-51 Mustang.” In Wikipedia, October 19, 2020. https://en.wikipedia.org/w/index.php?title=North_American_P-51_Mustang&oldid=984347874.")
A table from *WWII Aircraft Performance* gives combinations of flight parameters apparently for a version of the P-51, however it has no title or description, so we cannot be confident. [4](https://aiimpacts.org/energy-efficiency-of-north-american-p-51-mustang/#easy-footnote-bottom-4-2737 "“P-51D_15342_AppendixB.Pdf.” Accessed November 5, 2020. http://www.wwiiaircraftperformance.org/mustang/P-51D_15342_AppendixB.pdf.") We extracted some data from it [here](https://docs.google.com/spreadsheets/d/1RsewNj8d8JDlL9628xioi2vcVeG0oPMKlC8u59FVvA4/edit?usp=sharing). This data suggests the best combination of parameters gives a fuel economy of 6.7 miles/gallon (10.8km)

We don’t know what fuel was used, but fuel energy density seems likely to be between 31—39 MJ/L = 117—148 MJ/gallon.[5](https://aiimpacts.org/energy-efficiency-of-north-american-p-51-mustang/#easy-footnote-bottom-5-2737 "Wikipedia lists energy densities for a variety of fuels, and those for petroleum, 100LL avgas, diesel, and jet fuel are within this range and seem likely to be similar to that used.

“Energy Density.” In Wikipedia, September 21, 2020. https://en.wikipedia.org/w/index.php?title=Energy_density&oldid=979608484.")
Thus the plane flew about 10.8km on 117—148 MJ of fuel, for 0.073—0.092 m/kJ

### Mass.distance per Joule

We have:

* Distance per kilojoule: 0.073—0.092 m/kJ
* Mass: 3,465—5,488 kg

This gives us a range of 0.25 – 0.50 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----


Energy efficiency of Vickers Vimy plane

*Updated Nov 5, 2020*

The Vickers Vimy:

* flew around 0.025—0.050 m/kJ
* and moved mass at around 0.081 – 0.25 kg.m/J

Details
-------

The *Vickers Vimy* was a 1917 British WWI bomber.[1](https://aiimpacts.org/energy-efficiency-of-vickers-vimy-plane/#easy-footnote-bottom-1-2734 "“The Vickers Vimy was a British heavy bomber aircraft developed and manufactured by Vickers Limited. Developed during the latter stages of the First World War to equip the Royal Flying Corps (RFC), the Vimy was designed by Reginald Kirshaw “Rex” Pierson, Vickers’ chief designer…On 16 August 1917 Vickers was issued with a contract for three prototype aircraft…  the manufacture of the three prototypes was completed within four months.”

“Vickers Vimy.” In Wikipedia, October 27, 2020. https://en.wikipedia.org/w/index.php?title=Vickers_Vimy&oldid=985669067.") It was used in the [first non-stop transatlantic flight](https://aiimpacts.org/historic-trends-in-transatlantic-passenger-travel/).

### Mass

According to Wikipedia[2](https://aiimpacts.org/energy-efficiency-of-vickers-vimy-plane/#easy-footnote-bottom-2-2734 "“Vickers Vimy.” In Wikipedia, October 27, 2020. https://en.wikipedia.org/w/index.php?title=Vickers_Vimy&oldid=985669067."):

* **Empty weight:** 7,104 lb (3,222 kg)
* **Max takeoff weight:** 10,884 lb (4,937 kg)

We use the range 3,222—4,937 kg, since we do not know at what weight in that range the relevant speeds were measured.

### Energy use per second

We also have:

* **Power:** 360 horsepower = 270 kW[3](https://aiimpacts.org/energy-efficiency-of-vickers-vimy-plane/#easy-footnote-bottom-3-2734 "“Powerplant: 2 × Rolls-Royce Eagle VIII water-cooled V12 engines, 360 hp (270 kW) each”

“Vickers Vimy.” In Wikipedia, October 27, 2020. https://en.wikipedia.org/w/index.php?title=Vickers_Vimy&oldid=985669067.")
* **Efficiency of use of energy from fuel:** we did not find data on this, so use an estimate of 15%-30%, based on what we know about the [energy efficiency of the Wright Flyer](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#Efficiency_of_energy_conversion_from_fuel_to_motor_power).

From these we can calculate:

Energy use per second
= power of engine x 1/efficiency in converting energy to engine power
= 270kJ/s / .15—270kJ/s / .30
= 900—1800 kJ/s

### Distance per second

Wikipedia gives us:

* ****Maximum speed:****100 mph (160 km/h, 87 kn)[4](https://aiimpacts.org/energy-efficiency-of-vickers-vimy-plane/#easy-footnote-bottom-4-2734 "“Wright Model B.” In Wikipedia, September 16, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Model_B&oldid=978792334.")

Note that the figures for power do not obviously correspond to the highest measured speed. This is a rough estimate.

### Distance per Joule

We now have (from above):

* speed = 100 miles/h = 44.7m/s
* energy use = 900—1800 kJ/s

Thus, on average each second the plane flies 44.7 m and uses 900—1800 kJ, for 0.025—0.050 m/kJ.

### Mass.distance per Joule

We have:

* Distance per kilojoule: 0.025—0.050 m/kJ
* Mass: 3,222—4,937 kg

This gives us a range of 0.081 – 0.25 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----

Energy efficiency of Vickers Vimy plane


Energy efficiency of Wright model B

*Updated Nov 5, 2020*

The Wright model B:

* flew around 0.10—0.21m/kJ
* and moved mass at around 0.036 – 0.12 kg.m/J

Details
-------

The *Wright Model B* was a 1910 plane developed by the Wright Brothers.[1](https://aiimpacts.org/energy-efficiency-of-wright-model-b/#easy-footnote-bottom-1-2731 "“The Wright Model B was an early pusher biplane designed by the Wright brothers in the United States in 1910. It was the first of their designs to be built in quantity. “

“Wright Model B.” In Wikipedia, September 16, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Model_B&oldid=978792334.")
### Mass

According to Wikipedia[2](https://aiimpacts.org/energy-efficiency-of-wright-model-b/#easy-footnote-bottom-2-2731 "“Wright Model B.” In Wikipedia, September 16, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Model_B&oldid=978792334."):

* **Empty weight:** 800 lb (363 kg)
* **Gross weight:** 1,250 lb (567 kg)

We use the range 363—567 kg, since we do not know at what weight in that range the relevant speeds were measured.

### Energy use per second

From Wikipedia, we have[3](https://aiimpacts.org/energy-efficiency-of-wright-model-b/#easy-footnote-bottom-3-2731 "“Wright Model B.” In Wikipedia, September 16, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Model_B&oldid=978792334."):

* **Power:** 35 horsepower = 26kW
* **Efficiency of use of energy from fuel:** we could not find data on this, so use an estimate of 15%-30%, based on what we know about the [energy efficiency of the Wright Flyer](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#Efficiency_of_energy_conversion_from_fuel_to_motor_power).

From these we can calculate:

Energy use per second
= power of engine x 1/efficiency in converting energy to engine power
= 26kJ/s / .15—26kJ/s / .30
= 86.6—173 kJ/s

### Distance per second

Wikipedia gives us[4](https://aiimpacts.org/energy-efficiency-of-wright-model-b/#easy-footnote-bottom-4-2731 "“Wright Model B.” In Wikipedia, September 16, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Model_B&oldid=978792334."):

* **Maximum speed:** 45 mph (72 km/h, 39 kn)
* **Cruise speed:** 40 mph (64 km/h, 35 kn)

We use the cruise speed, as it seems more likely to represent speed achieved with the energy usages reported.

### Distance per Joule

We now have (from above):

* speed = 40miles/h = 17.9m/s
* energy use = 86.6—173 kJ/s

Thus, on average each second the plane flies 17.9m and uses 86.6—173 kJ, for 0.10—0.21m/kJ.

### Mass.distance per Joule

We have:

* Distance per kilojoule: 0.10—0.21m/kJ
* Mass: 363—567kg

This gives us a range of 0.036 – 0.12 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----

Energy efficiency of Wright model B


Energy efficiency of Wright Flyer

*Updated Dec 10, 2020*

The Wright Flyer:

* flew around 0.080-0.18m/kJ
* and moved mass at around .022 – .061 kg.m/J

Details
-------

The *Wright Flyer* (*Flyer I*) was the first successful plane, built in 1903.[1](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-1-2729 "“The Wright Flyer (often retrospectively referred to as Flyer I or 1903 Flyer) was the first successful heavier-than-air powered aircraft….The Wrights built the aircraft in 1903 using giant spruce wood as their construction material.[2]“

“Wright Flyer.” In Wikipedia, October 30, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Flyer&oldid=986246127.")
### Mass

According to Wikipedia[2](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-2-2729 "“Wright Flyer.” In Wikipedia, October 30, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Flyer&oldid=986246127."):

* **Empty weight:** 605 lb (274 kg)
* **Max takeoff weight:** 745 lb (338 kg)

### Energy use per second

#### Fuel use per hour

A 1904 article in the Minneapolis Journal says the plane consumed ‘a little less than than ten pounds of gasoline per hour’.[3](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-3-2729 "“At the speed of 1200 revolutions per minute the engine develops sixteen-brake horsepower, with a consumption of a little less than ten pounds of gasoline per hour.” ") A pound of gasoline contains around 20MJ[4](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-4-2729 "“Gasoline has an energy density of about 45 megajoules per kilogram (MJ/kg)”

“Energy Density of Gasoline – The Physics Factbook.” Accessed November 3, 2020. https://hypertextbook.com/facts/2003/ArthurGolnik.shtml.

45MJ/kg = 20.4MJ/lb") So we have:

Hourly fuel consumption: 10lb/h x 20MJ/lb = 200MJ/h = 55kJ/s

We don’t know how reliable this source is. For instance, a 1971 book, *The Write Brothers’ Engines and their Design* does not give data on fuel consumption in their table of engine characteristics for lack of available comprehensive data[5](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-5-2729 "“No fuel consumption figures are given, primarily because no comprehensive data have been found. This is most probably because in the early flight years, when the Wrights were so meticulously measuring and recording technical information on the important factors affecting their work, the flights were of such short duration that fuel economy was of very minor importance.”

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm."), suggesting that its authors did not consider the article strong evidence, though it is also possible that they didn’t have access to the 1904 article.

#### Utilized motor power / efficiency

To confirm, we can estimate the plane’s energy use per second by a second means: combining the claimed power (energy/second) made use of by the engine, and a guess about how much fuel is needed to deliver that amount of energy.

##### Utilized motor power

According to Wikipedia, the plane had a 12 horsepower (9 kJ/s), gasoline engine.[6](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-6-2729 "“Since they could not find a suitable automobile engine for the task, they commissioned their employee Charlie Taylor to build a new design from scratch, effectively a crude 12-horsepower (9-kilowatt) gasoline engine.[4]

“Wright Flyer.” In Wikipedia, October 30, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Flyer&oldid=986246127.") The 1904 Minneapolis Journal article put it at 16 horsepower (12 kJ/s), and Orville Wright, quoted by Hobbs (1971), puts it at ‘almost 16 horsepower’ at one point.[7](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-7-2729 "“Speaking of the first engine, Orville Wright wrote, “Since putting in heavier springs to actuate the valves on our engine we have increased its power to nearly 16 hp and at the same time reduced the amount of gasoline consumed per hour to about one-half of what it was.””

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm.") Hobbs says that at one point this engine achieved 25 horsepower, though this probably isn’t representative of what was ‘actually utilized’.[8](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-8-2729 "“In the table, performance is given in ranges which are thought to be the most representative of those actually utilized. Occasionally performances were attained even beyond the ranges given. For example, the 4×4-in. flat development engine eventually demonstrated 25 hp at an MEP of approximately 65 psi.”

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm.") For that he gives a range of 8.25-16 horsepower.[9](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-9-2729 "See first table in Appendix. It appears that the lower number is for the first flight, though this is confusing:

“One important figure—the horsepower actually utilized during the first flight—is quite accurately known. In 1904 the 1904-1905 flight engine, after having been calibrated by their prony-brake test-fan method, was used to turn the 1903 flight propellers, and Orville Wright calculated this power to be 12.05 bhp by comparing the calibrated engine results with those obtained with the flight engine at Kitty Hawk when tested under similar conditions. However, since the tests were conducted in still air with the engine stationary, this did not exactly represent the flight condition. No doubt the rotational speed of the engine and propellers increased somewhat with the forward velocity of the airplane so that unless the power-rpm curve of the engine was flat, the actual horsepower utilized was probably a small amount greater than Orville’s figures. The lowest power figure shown for this engine is that of its first operation.”

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm.") In light of these estimates, we will use 8.25-16 horsepower, which is 6.15-12 kJ/s.

##### Efficiency of energy conversion from fuel to motor power

A quote from Orville Wright suggests fuel consumption as 0.580lb of fuel per horsepower hour.[10](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-10-2729 "“Orville Wright quotes an early figure of brake thermal efficiency for the 1903 engine that gives a specific fuel consumption of .580 lb of fuel per bhp/hr based on an estimate of the heating value of the fuel they had. This seems low, considering the compression ratio and probable leakage past their rather weak piston rings, but it is possible.”

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm.

Note that the quote says bhp/h, but we think it must mean bhp.h.

Also, bhp is ‘brake horsepower’, meaning horsepower measured empirically through a particular mechanism:

‘Brake horsepower (bhp) is the power measured using a brake type (load) dynamometer at a specified location, such as the crankshaft, output shaft of the transmission, rear axle or rear wheels.’

“Horsepower.” In Wikipedia, November 3, 2020. https://en.wikipedia.org/w/index.php?title=Horsepower&oldid=986863945. ") This would imply 23% of energy was utilized from the fuel.[11](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-11-2729 "fuel/power = 0.580lb fuel / hp.h
= 0.580 * 20MJ / hp.h
= 11.6MJ/ 745J.h/s
= 11600kJ / (0.745 * 3600 kJ)
= 4.3.

Thus power/fuel = 0.23.")
Hobbs notes that this seems low, but assumes a similar efficiency: 24.50%. Thus he presumably doesn’t find it implausible.[12](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-12-2729 "“Assuming a rich mixture, consumption of all the air, and an airbrake thermal efficiency of 24.50% for the original engine…”

Hobbs, Leonard S. The Wright Brothers’ Engines and Their Design. [For sale by Supt. of Docs., U.S. Govt. Print. Off.]; First Edition. Smithsonian Institution Press, 1971. https://www.gutenberg.org/files/38739/38739-h/38739-h.htm.")
According to Wikipedia, the thermal efficiency of a typical gasoline engine is 20%[13](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-13-2729 "“Typically, most petrol engines have approximately 20%(avg.) thermal efficiency, which is nearly half of diesel engines. However some newer engines are reported to be much more efficient (thermal efficiency up to 38%) than previous spark-ignition engines.[5]“

“Petrol Engine.” In Wikipedia, August 20, 2020. https://en.wikipedia.org/w/index.php?title=Petrol_engine&oldid=973981680."). It seems that this has increased[14](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-14-2729 "See above note."), which would suggest that the typical figure was lower in 1903. We don’t think this undermines the more specific figures given above.

It seems likely that Hobbs number is best here, since he knows about Wright’s number, and may have more information than us about for instance the exact fuel being used. So we use 24.5%.

##### Calculation of energy use from motor power/efficiency

Combining these numbers, we have:

power spent = 6.15-12 kJ/s used by engine x 1 / 24.5% fuel energy needed to get one unit of energy used by engine, given inefficiency

= 25-49 kJ/s

#### Calculation of energy use

We now have:

* energy expenditure calculated via motor power and efficiency: 25-49 kJ/s
* energy expenditure calculated via hourly fuel use: 55kJ/s

Neither figure seems clearly more reliable, so we will use the range 25-55kJ/s

### Distance per second

Two of the Wright Flyer’s first flights were 120 feet in 12 seconds and 852 feet in 59 seconds.[15](https://aiimpacts.org/energy-efficiency-of-wright-flyer/#easy-footnote-bottom-15-2729 "“His first flight lasted 12 seconds for a total distance of 120 feet (37 m) – shorter than the wingspan of a Boeing 747, as noted by observers in the 2003 commemoration of the first flight.[1][5]…The last flight, by Wilbur, was 852 feet (260 m) in 59 seconds, much longer than each of the three previous flights of 120, 175 and 200 feet (37, 53 and 61 m).”

“Wright Flyer.” In Wikipedia, October 30, 2020. https://en.wikipedia.org/w/index.php?title=Wright_Flyer&oldid=986246127.") This gives speeds of 3m/s and 4.4m/s. We will use the second, since it better represents successful flight, still within the first days.

### Distance per Joule

We now have (from above):

* speed = 4.4 m/s
* energy use = 25-55 kJ/s

Thus, on average each second the plane flies 4.4m and uses 25-55kJ, for 0.080-0.18m/kJ.

### Mass.distance per Joule

We have:

* Distance per kilojoule: 0.080-0.18m/kJ
* Mass: 274-338kg

This gives us a range of .022 – .061 kg.m/J

*Primary author: Ronny Fernandez*

Notes
-----

Energy efficiency of Wright Flyer


Automated intelligence is not AI

*By Katja Grace, 1 November 2020, Crossposted from [world spirit sock puppet](https://worldspiritsockpuppet.com).*

Sometimes we think of ‘artificial intelligence’ as whatever technology ultimately automates human cognitive labor.

I question this equivalence, looking at past automation. In practice human cognitive labor is replaced by things that don’t seem at all cognitive, or like what we otherwise mean by AI.

Some examples:

1. Early in the existence of bread, it might have been toasted by someone holding it close to a fire and repeatedly observing it and recognizing its level of doneness and adjusting. Now we have machines that hold the bread exactly the right distance away from a predictable heat source for a perfect amount of time. You could say that the shape of the object embodies a lot of intelligence, or that intelligence went into creating this ideal but non-intelligent tool.
2. Self-cleaning ovens replace humans cleaning ovens. Humans clean ovens with a lot of thought—looking at and identifying different materials and forming and following plans to remove some of them. Ovens clean themselves by getting very hot.
3. Carving a rabbit out of chocolate takes knowledge of a rabbit’s details, along with knowledge of how to move your hands to translate such details into chocolate with a knife. A rabbit mold automates this work, and while this route may still involve intelligence in the melting and pouring of the chocolate, all rabbit knowledge is now implicit in the shape of the tool, though I think nobody would call a rabbit-shaped tin ‘artificial intelligence’.
4. Human pouring of orange juice into glasses involves various mental skills. For instance, classifying orange juice and glasses and judging how they relate to one another in space, and moving them while keeping an eye on this. Automatic orange juice pouring involves for instance a button that can only be pressed with a glass when the glass is in a narrow range of locations, which opens an orange juice faucet running into a spot common to all the possible glass-locations.

Some of this is that humans use intelligence where they can use some other resource, because it is cheap on the margin where the other resource is expensive. For instance, to get toast, you could just leave a lot of bread at different distances then eat the one that is good. That is bread-expensive and human-intelligence-cheap (once you come up with the plan at least). But humans had lots of intelligence and not much bread. And if later we automate a task like this, before we have computers that can act very similarly to brains, then the alternate procedure will tend to be one that replaces human thought with something that actually is cheap at the time, such as metal.

I think a lot of this is that to deal with a given problem you can either use flexible intelligence in the moment, or you can have an inflexible system that happens to be just what you need. Often you will start out using the flexible intelligence, because being flexible it is useful for lots of things, so you have some sitting around for everything, whereas you don’t have an inflexible system that happens to be just what you need. But if a problem seems to be happening a lot, it can become worth investing the up-front cost of getting the ideal tool, to free up your flexible intelligence again.

Automated intelligence is not AI


Time for AI to cross the human range in English draughts

*Updated 26 Oct 2020*

AI progress in English draughts performance crossed the following ranges in the following times:

|  |  |  |  |
| --- | --- | --- | --- |
| **Range** | **Start** | **End** | **Duration (years)** |
| First attempt to beginner level | 1951 | ~1956, <1961 | ~4, <10 |
| Beginner to superhuman | ~1956, <1961 | 1994 | ~38, >33 |
| Above superhuman | 1994 | 2007\* | 13\* |

\* treating perfect play as the end of progress, though progress could potentially be made in performing better against imperfect play.

Details
-------

### Metric

‘English Draughts’ is a popular variety of draughts, or checkers.

Here we look at direct success of AI in beating human players, rather than measuring humans and AI on a separate metric of strength.

### Data

Data here comes mostly from Wikipedia. We found several discrepancies in Wikipedia’s accounts of these events, so consider the remaining data to be somewhat unreliable.

### AI achievement of human milestones

#### Earliest attempt

According to Wikipedia, the first checkers program was run in 1951.[1](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-1-2704 "“The first English draughts computer program was written by Christopher Strachey, M.A. at the National Physical Laboratory, London.[5] Strachey finished the programme, written in his spare time, in February 1951. It ran for the first time on NPL’s Pilot ACE on 30 July 1951. He soon modified the programme to run on the Manchester Mark 1.”

“English Draughts.” In Wikipedia, October 8, 2020. https://en.wikipedia.org/w/index.php?title=English_draughts&oldid=982525532.")
#### Beginner level

There seems to be some ambiguity around the timing and performance of Arthur Samuel’s early draughts programs, but it appears that he worked on them from around 1952. In 1956, he demonstrated a program on television. [2](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-2-2704 "“It didn’t take long before Samuel had a program that played a respectable game of checkers, capable of easily defeating novice players. It was first publicly demonstrated on television on February 24, 1956. Thomas Watson, President of IBM, arranged for the program to be exhibited to shareholders. He predicted that it would result in a fifteen-point rise in the IBM stock price. It did.”

Schaeffer, Jonathan. One Jump Ahead: Challenging Human Supremacy in Checkers. 1st Edition. New York: Springer, 1997.

quoted in:

“Legacy – Chinook – World Man-Machine Checkers Champion.” Accessed October 26, 2020. http://webdocs.cs.ualberta.ca/~chinook/project/legacy.html.") It is unclear how good the program’s play was, but it is said to have resulted in a fifteen-point rise in the stock price of IBM when demonstrated to IBM shareholders, seemingly at around that time. This weakly suggests that the program played at at least beginner level.

In 1962 Samuel’s program apparently beat an ambiguously skilled player who would by four-years later become a state champion in Connecticut.[3](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-3-2704 "The historical record is fuzzy, but for some reason he chose to have his program debut against Robert Nealey a blind checkers champion from Stamford, Connecticut. IBM’s Research News claimed that Nealey was “a former Connecticut checkers champion, and one of the nation’s foremost players.”

Although a self-proclaimed master, Nealey’s tournament results never justified such a claim. At the time of the game, he was not a former Connecticut state champion, although he did win the title in 1966, four years after the game with Samuel’s program. In the history of the state championship, no recognized master had won the event. Nealey didn’t play in any of the premier checkers events, such as the U.S. championship, and apparently acquired his reputation by beating local players.”

Schaeffer, Jonathan. One Jump Ahead: Challenging Human Supremacy in Checkers. 1st Edition. New York: Springer, 1997.

quoted in:

“Legacy – Chinook – World Man-Machine Checkers Champion.” Accessed October 26, 2020. http://webdocs.cs.ualberta.ca/~chinook/project/legacy.html.") Thus progress was definitely beyond beginner level by 1962.

#### Superhuman level

In 1994, computer program Chinook drew six times against world champion Marius Tinsley, before Tinsley withdrew due to pancreatic cancer and Chinook officially won.[4](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-4-2704 "“In a rematch, Chinook was declared the Man-Machine World Champion in checkers in 1994 in a match against Marion Tinsley after six drawn games, and Tinsley’s withdrawal due to pancreatic cancer. While Chinook became the world champion, it never defeated the best checkers player of all time, Tinsley, who was significantly superior to even his closest peer.[1]“

“Chinook (Computer Program).” In Wikipedia, August 24, 2020. https://en.wikipedia.org/w/index.php?title=Chinook_(computer_program)&oldid=974711515.") Thus Chinook appears to have been close to as good as the best player in 1994.

#### End of progress

In 2007 checkers was ‘weakly solved’, which is to say that perfect play guaranteeing a draw for both sides from the start of the game is known, from the starting state[5](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-5-2704 "“English draughts was weakly solved in 2007 by the team of Canadian computer scientist Jonathan Schaeffer. From the standard starting position, both players can guarantee a draw with perfect play.”

“Draughts.” In Wikipedia, October 25, 2020. https://en.wikipedia.org/w/index.php?title=Draughts&oldid=985336948.") (this does not imply that if someone plays imperfectly, perfect moves following this are known).[6](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-english-draughts/#easy-footnote-bottom-6-2704 "“A two-player game can be solved on several levels:[1][2]…
Weak
Provide an algorithm that secures a win for one player, or a draw for either, against any possible moves by the opponent, from the beginning of the game. That is, produce at least one complete ideal game (all moves start to end) with proof that each move is optimal for the player making it. It does not necessarily mean a computer program using the solution will play optimally against an imperfect opponent.”

“Solved Game.” In Wikipedia, September 11, 2020. https://en.wikipedia.org/w/index.php?title=Solved_game&oldid=977794097.") This is not the best possible performance by all measures, since further progress could presumably be made on reliably beating worse players.

### Times for AI to cross human-relative ranges

Given the above dates, we have:

|  |  |  |  |
| --- | --- | --- | --- |
| **Range** | **Start** | **End** | **Duration (years)** |
| First attempt to beginner level | 1951 | ~1956, <1961 | ~4, <10 |
| Beginner to superhuman | ~1956, <1961 | 1994 | ~38, >33 |
| Above superhuman | 1994 | 2007\* | 13\* |

\* treating perfect play as the end of progress, though progress could potentially be made in performing better against imperfect play.

**Primary author: Katja Grace**

Notes
-----


Time for AI to cross the human range in StarCraft

*Published 20 Oct 2020; updated 22 Oct 2020*

Progress in AI StarCraft performance took:

* ~0 years to reach the level of an untrained human
* ~21 years to pass from beginner level to high professional human level
* ~2 years to continue from trained human to current performance (2020), with no particular end in sight.

Details
-------

### Metric

We compare human and AI players on their direct ability to beat one another (rather than a measure of the overall performance of each).

### AI milestones

#### Earliest attempt

Starcraft was released in 1998[1](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-starcraft/#easy-footnote-bottom-1-2684 "“The series debuted with the video game StarCraft in 1998.”

“StarCraft.” In Wikipedia, September 29, 2020. https://en.wikipedia.org/w/index.php?title=StarCraft&oldid=980937551.") The game allows the player to play against a computer opponent, however this built-in AI has access to information that a normal player would not have. For instance, it has real-time information about what the other player is doing at all times, which is normally hidden. We do not have detailed knowledge about early StarCraft AIs that do not have this advantage, but our impression is that it was possible to write them from the start (see next section).

#### Beginner level

Our impression is that since StarCraft Brood War came out in 1998, it has been possible to write a bot that can beat a player who recently learned the game, without “cheating” in the way that the game’s built-in computer opponents do. This is uncertain, and based on private discussion with people who write Starcraft AIs that compete in tournaments.

#### Professional level

In 2018, DeepMind’s AlphaStar beat MaNa[2](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-starcraft/#easy-footnote-bottom-2-2684 "“In a series of test matches held on 19 December, AlphaStar decisively beat Team Liquid’s Grzegorz “MaNa” Komincz, one of the world’s strongest professional StarCraft players, 5-0, following a successful benchmark match against his team-mate Dario “TLO” Wünsch. The matches took place under professional match conditions on a competitive ladder map and without any game restrictions.”

Deepmind. “AlphaStar: Mastering the Real-Time Strategy Game StarCraft II.” Accessed October 22, 2020. /blog/article/alphastar-mastering-real-time-strategy-game-starcraft-ii."), a strong professional player (seemingly 13th place in the 2018 StarCraft II World Championship Series Circuit)[3](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-starcraft/#easy-footnote-bottom-3-2684 "Liquipedia StarCraft 2 Wiki. “2018 StarCraft II World Championship Series Circuit: Standings.” Accessed October 20, 2020. https://liquipedia.net/starcraft2/2018_StarCraft_II_World_Championship_Series_Circuit/Standings."). This does not imply that AlphaStar was in general a stronger player than MaNa, but suggests AlphaStar was at a broadly high professional level. How AlphaStar’s performance compares to humans will depend on how narrowly the task is defined, so that if the AI is not allowed to give commands faster than a human is able, it will compare less favorably than if it is allowed to give commands very quickly[4](https://aiimpacts.org/time-for-ai-to-cross-the-human-range-in-starcraft/#easy-footnote-bottom-4-2684 "AI Impacts researcher Rick Korzekwa details this controversy in a blog post:

“The Unexpected Difficulty of Comparing AlphaStar to Humans – AI Impacts.” Accessed October 22, 2020. https://aiimpacts.org/the-unexpected-difficulty-of-comparing-alphastar-to-humans/.").

### Times for AI to cross human-relative ranges

Given the above dates, we have:

|  |  |  |  |
| --- | --- | --- | --- |
| **Range** | **Start** | **End** | **Duration (years)** |
| First attempt to beginner level | 1998 | 1998 | ~0 |
| Beginner to superhuman | 1998 | 2018 | ~21 |
| Above superhuman | 2018 | ? | >2 |

*Primary author: Rick Korzekwa*

Notes
-----


Time for AI to cross the human performance range in ImageNet image classification

*Published 19 Oct 2020*

Progress in computer image classification performance took:

* Over 14 years to reach the level of an untrained human
* 3 years to pass from untrained human level to trained human level
* 5 years to continue from trained human to current performance (2020)

Details
-------

### Metric

ImageNet[1](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-1-2683 "“ImageNet is an image database organized according to the WordNet hierarchy (currently only the nouns), in which each node of the hierarchy is depicted by hundreds and thousands of images. Currently we have an average of over five hundred images per node. “

“ImageNet.” Accessed October 19, 2020. http://www.image-net.org/.") is a large collection of images organized into a hierarchy of noun categories. We looked at ‘top-5 accuracy’ in categorizing images. In this task, the player is given an image, and can guess five different categories that the image might represent. It is judged as correct if the image is in fact in any of those five categories.

### Human performance milestones

#### Beginner level

We used Andrej Karpathy’s interface[2](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-2-2683 "Karpathy, Andrej. “Ilsvrc.” Accessed October 19, 2020. https://cs.stanford.edu/people/karpathy/ilsvrc/.") for doing the ImageNet top-5 accuracy task ourselves, and asked a few friends to do it. Five people did it, with performances ranging from 74% to 89%, with a median performance of 81%.

This was not a random sample of people, and conditions for taking the test differed. Most notably, there was no time limit, so time allocated was set by patience for trying to marginally improve guesses.

#### Trained human-level

ImageNet categorization is not a popular activity for humans, so we do not know what highly talented and trained human performance would look like. The best relatively high human performance measure we have comes from Russakovsky et al, who report on performance of two ‘expert annotators’, who they say learned many of the categories. [3](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-3-2683 "‘Therefore, in evaluating the human accuracy we relied primarily on expert annotators who learned to recognize a large portion of the 1000 ILSVRC classes. During training, the annotators labeled a few hundred validation images for practice and later switched to the test set images’

Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. “ImageNet Large Scale Visual Recognition Challenge.” ArXiv:1409.0575 [Cs], January 29, 2015. http://arxiv.org/abs/1409.0575.") The better performing annotator there had a 5.1% error rate.[4](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-4-2683 "“Annotator A1 evaluated a total of 1500 test set images. The GoogLeNet classication error on this sample was estimated to be 6.8% (recall that the error on full test set of 100,000 images is 6.7%, as shown in Table 7). The human error was estimated to be 5.1%.”

Also see Table 9

Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. “ImageNet Large Scale Visual Recognition Challenge.” ArXiv:1409.0575 [Cs], January 29, 2015. http://arxiv.org/abs/1409.0575.")
### AI achievement of human milestones

#### Earliest attempt

The ImageNet database was released in 2009.[5](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-5-2683 "“They presented their database for the first time as a poster at the 2009 Conference on Computer Vision and Pattern Recognition (CVPR) in Florida.”

“ImageNet.” In Wikipedia, September 9, 2020. https://en.wikipedia.org/w/index.php?title=ImageNet&oldid=977585441.
"). An annual contest, the ImageNet Large Scale Visual Recognition Challenge, began in 2010.[6](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-6-2683 "“…The ImageNet Large Scale Visual Recognition Challenge (ILSVRC) has been running annually for five years (since 2010) and has become the standard benchmark for large-scale object recognition.”

Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. “ImageNet Large Scale Visual Recognition Challenge.” ArXiv:1409.0575 [Cs], January 29, 2015. http://arxiv.org/abs/1409.0575.")
In the 2010 contest, the best top-5 classification performance had 28.2% error.[7](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-7-2683 "See table 6.

Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. “ImageNet Large Scale Visual Recognition Challenge.” ArXiv:1409.0575 [Cs], January 29, 2015. http://arxiv.org/abs/1409.0575.")

However image classification broadly is older. Pascal VOC was a similar previous contest, which ran from 2005.[8](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-8-2683 "“The PASCAL Visual Object Classes (VOC) challenge is a benchmark in visual object category recognition and detection, providing the vision and machine learning communities with a standard dataset of images and annotation, and standard evaluation procedures. Organised annually from 2005 to present, the challenge and its associated dataset has become accepted as the benchmark for object detection.”

Everingham, Mark, Luc Van Gool, Christopher K. I. Williams, John Winn, and Andrew Zisserman. “The Pascal Visual Object Classes (VOC) Challenge.” International Journal of Computer Vision 88, no. 2 (June 2010): 303–38. https://doi.org/10.1007/s11263-009-0275-4.") We do not know when the first successful image classification systems were developed. In a blog post, Amidi & Amidi point to LeNet as pioneering work in image classification[9](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-9-2683 "See section ‘LeNet’.

“The Evolution of Image Classification Explained.” Accessed October 19, 2020. https://stanford.edu/~shervine/blog/evolution-image-classification-explained#lenet."), and it appears to have been developed in 1998.[10](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-10-2683 "“LeNet is a convolutional neural network structure proposed by Yann LeCun et al. in 1998.”

“LeNet.” In Wikipedia, June 19, 2020. https://en.wikipedia.org/w/index.php?title=LeNet&oldid=963418885.")
#### Beginner level

The first entrant in the ImageNet contest to perform better than our beginner level benchmark was SuperVision (commonly known as AlexNet) in 2012, with a 15.3% error rate.[11](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-11-2683 "“We also entered a variant of this model in the
ILSVRC-2012 competition and achieved a winning top-5 test error rate of 15.3%”

Krizhevsky, Alex, Ilya Sutskever, and Geoffrey E Hinton. “ImageNet Classification with Deep Convolutional Neural Networks.” In Advances in Neural Information Processing Systems 25, edited by F. Pereira, C. J. C. Burges, L. Bottou, and K. Q. Weinberger, 1097–1105. Curran Associates, Inc., 2012. http://papers.nips.cc/paper/4824-imagenet-classification-with-deep-convolutional-neural-networks.pdf.

Also, see Table 6 for a list of other entrants:

Russakovsky, Olga, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, et al. “ImageNet Large Scale Visual Recognition Challenge.” ArXiv:1409.0575 [Cs], January 29, 2015. http://arxiv.org/abs/1409.0575.")
#### Superhuman level

In 2015 He et al apparently achieved a 4.5% error rate, slightly better than our high human benchmark.[12](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-12-2683 "“Our 152-layer ResNet has a single-model top-5 validation error of 4.49%.”

Also see Table 4

He, Kaiming, Xiangyu Zhang, Shaoqing Ren, and Jian Sun. “Deep Residual Learning for Image Recognition.” ArXiv:1512.03385 [Cs], December 10, 2015. http://arxiv.org/abs/1512.03385.")
#### Current level

According to paperswithcode.com, performance has continued to climb, to 2020, though slower than earlier.[13](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-imagenet-image-classification/#easy-footnote-bottom-13-2683 "See figure:

“Papers with Code – ImageNet Benchmark (Image Classification).” Accessed October 19, 2020. https://paperswithcode.com/sota/image-classification-on-imagenet.")
### Times for AI to cross human-relative ranges

Given the above dates, we have:

|  |  |  |  |
| --- | --- | --- | --- |
| Range | Start | End | Duration (years) |
| First attempt to beginner level | <1998 | 2012 | >14 |
| Beginner to superhuman | 2012 | 2015 | 3 |
| Above superhuman | 2015 | >2020 | >5 |

*Primary author: Rick Korzekwa*

Notes
-----


Time for AI to cross the human performance range in Go

*Posted 15 Oct 2020; updated 19 Oct 2020*

Progress in computer Go performance took:

* 0-19 years to go from the first attempt to playing at human beginner level (<1987)
* >30 years to go from human beginner level to superhuman level (<1987-2017)
* 3 years to go from superhuman level to the the current highest performance (2017-2020)

Details
-------

### Human performance milestones

Human go ratings range from 30 kyu (beginner), through 7 dan to at least 9 professional dan.[1](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-1-2680 "“Go Ranks and Ratings.” In Wikipedia, June 20, 2020. https://en.wikipedia.org/w/index.php?title=Go_ranks_and_ratings&oldid=963489455.") These ratings go downwards through kyu levels, then upward through dan levels, then upward through professional dan levels. The top ratings seem to be [closer together](http://en.wikipedia.org/wiki/Go_ranks_and_ratings#Elo-like_rating_systems_as_used_in_Go) than the lower ones, though there are apparently [multiple systems](https://en.wikipedia.org/wiki/Go_ranks_and_ratings#Winning_probabilities) which vary)[2](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-2-2680 "See table:

“Go Ranks and Ratings.” In Wikipedia, June 20, 2020. https://en.wikipedia.org/w/index.php?title=Go_ranks_and_ratings&oldid=963489455.")
### AI achievement of human milestones

#### Earliest attempt

Wikipedia says the first Go program was written in 1968.[3](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-3-2680 "“The first Go program was written by Albert Lindsey Zobrist in 1968 as part of his thesis on pattern recognition.[11] It introduced an influence function to estimate territory and Zobrist hashing to detect ko.”") We do not know how well it performed.

#### Beginner level

We have not investigated early Go performance in depth. Figure 1 includes informed guesses about early performance by David Fotland, author of successful Go program, *The Many Faces of Go*, and *Sensei’s Library*, a Go wiki.[4](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-4-2680 "“Figure 25 shows estimates from two
sources: David Fotland—author of The Many Faces of Go, an Olympiad-winning Go program—and Sensei’s Library, a collaborative Go wiki. David Fotland warns that the data from before bots played on KGS is poor, as programs tended not to play in human tournaments and so failed to get ratings.”

Grace, Katja. “Algorithmic Progress in Six Domains.” Berkeley, CA: Machine Intelligence Research Institute, 2013.") Fotland says that early data on AI Go performance is poor, since bots did not play in tournaments, so were not rated.

![](http://aiimpacts.org/wp-content/uploads/2014/12/gobothistory-copy-1024x743.jpg)**Figure 1**: From [Grace 2013](http://intelligence.org/files/AlgorithmicProgress.pdf).
This suggests that by 1987 Go bots were performing better than human beginners. We do not have evidence to pin down the date of human beginner level AI better, but have also not investigated thoroughly (there appears to be more evidence).

#### Superhuman level

In May 2017 AlphaGo beat the top ranked Go player in the world.[5](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-5-2680 "“In May 2017, AlphaGo beat Ke Jie, who at the time was ranked top in the world,[27][28] in a three-game match during the Future of Go Summit.[29]“

“Computer Go.” In Wikipedia, July 27, 2020. https://en.wikipedia.org/w/index.php?title=Computer_Go&oldid=969736537") This does not imply that AlphaGo was overall better, but a new version in October could beat the May version in 89 games out of 100[6](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-go/#easy-footnote-bottom-6-2680 "“In October 2017, DeepMind revealed a new version of AlphaGo, trained only through self play, that had surpassed all previous versions, beating the Ke Jie version in 89 out of 100 games.[30]“

“Computer Go.” In Wikipedia, July 27, 2020. https://en.wikipedia.org/w/index.php?title=Computer_Go&oldid=969736537"), suggesting that if in May it would have beaten Ke Jie in more than 11% of games, the new version would beat Ke Jie more than half the time, i.e. perform better than the best human player. Thus 2017 seems like a reasonable date for top human-level play.

### Times for AI to cross human-relative ranges

Given the above dates, we have:

|  |  |  |  |
| --- | --- | --- | --- |
| Range | Start | End | Duration (years) |
| First attempt to beginner level | 1968 | <1987 | <19 |
| Beginner to superhuman | <1987 | 2017 | >30 |
| Above superhuman | 2017 | >2020 | >3 |

**Primary author: Katja Grace**

Notes
-----


Time for AI to cross the human performance range in chess

**Published 15 Oct 2020**

Progress in computer chess performance took:

* ~0 years to go from from playing chess at all to playing it at human beginner level
* ~49 years to go from human beginner level to superhuman level
* ~11 years to go from superhuman level to the the current highest performance

Details
-------

### Human range performance milestones

We use the common Elo system for measuring chess performance. Human chess Elo ratings range from around 800 (beginner)[1](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-1-2673 "“In general, a beginner (non-scholastic) is 800, the average player is 1500, and professional level is 2200.”

“Elo Rating System.” In Wikipedia, October 12, 2020. https://en.wikipedia.org/w/index.php?title=Elo_rating_system&oldid=983064897.") to 2882 (highest recorded).[2](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-2-2673 " “Table of top 20 rated players of all-time, with date their best ratings were first achieved…1 2882 Magnus Carlsen May 2014 23 years, 5 months”

“Comparison of Top Chess Players throughout History.” In Wikipedia, July 27, 2020. https://en.wikipedia.org/w/index.php?title=Comparison_of_top_chess_players_throughout_history&oldid=969714742.") The highest recorded human score is likely higher than it would have been without chess AI existing, since top players can learn from the AI.[3](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-3-2673 "For instance, the highest ranked player Magnus Carlsen has called AlphaZero his hero, and his strategy was noted by some to be reminiscent of it:

“This original strategy drew comparisons with the neural network program Alphazero, which Carlsen called his “hero” in a recent interview.”

the Guardian. “Chess: Magnus Carlsen Scores in Alphazero Style in Hunt for Further Records,” June 28, 2019. http://www.theguardian.com/sport/2019/jun/28/chess-magnus-carlsen-scores-in-alphazero-style-hunts-new-record.")

### Times for machines to cross ranges

#### Beginner to superhuman range

We could not find transparent sources for low computer chess Elo records, but it seems common to place Elo scores of 800-1200 in the 1950s and 1960s. In his book *Robot* (1999)[/note]Moravec, Hans. *Robot: Mere Machine to Transcendent Mind*, n.d., p71, also at <https://frc.ri.cmu.edu/~hpm/book97/ch3/index.html>[/note], Moravec gives the diagram shown in Figure 1, which puts a machine with an Elo of around 800 in 1957. He does not appear to provide a source for this however. Figure 2 shows another figure without sources from a 2002 article by L. Stephen Coles at Dr. Dobbs [4](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-4-2673 "“Computer Chess: The Drosophila of AI | Dr Dobb’s.” Accessed October 13, 2020. https://www.drdobbs.com/parallel/computer-chess-the-drosophila-of-ai/184405171?pgno=2. p2"), which puts some machine at over 1000 in around 1950. To err on the side of assuming narrow human ranges, and because Moravec appears to be a more reliable source, we use his data here. This means that machine chess performance entered the human range in 1957 at the latest.

![](https://frc.ri.cmu.edu/~hpm/book97/ch3/chess.plot.150.jpg)**Figure 1:** Graph from Moravec, 1999[5](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-5-2673 "Moravec, Hans. Robot: Mere Machine to Transcendent Mind, n.d., p71, also at https://frc.ri.cmu.edu/~hpm/book97/ch3/index.html"). We did not find Moravec’s sources for these numbers.
![](http://aiimpacts.org/wp-content/uploads/2020/10/chess_progress_source_unknown.gif)**Figure 2:** Chess AI progress compared to human performance, from Coles 2002[6](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-6-2673 "“Computer Chess: The Drosophila of AI | Dr Dobb’s.” Accessed October 13, 2020. https://www.drdobbs.com/parallel/computer-chess-the-drosophila-of-ai/184405171?pgno=2. p2"). The image appears to confusingly claim that the present time is around 1993, in which case the right of the graph (after ‘now’) must be imagined, though it appears to be approximately correct.
The chess computer Deep Blue famously beat the then world-champion Kasparov under tournament conditions in 1997.[7](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-7-2673 "“Deep Blue versus Garry Kasparov.” In Wikipedia, October 1, 2020. https://en.wikipedia.org/w/index.php?title=Deep_Blue_versus_Garry_Kasparov&oldid=981337286.") However this does not imply that Deep Blue was at that point overall more capable than Kasparov, i.e. had a higher Elo rating.[8](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-8-2673 "A group of Redditors discuss:

reddit. “R/Chess – Deep Blue’s True Elo Rating?” Accessed October 13, 2020. https://www.reddit.com/r/chess/comments/7bm361/deep_blues_true_elo_rating/.")
According to the [Swedish Chess Computer Association records](https://aiimpacts.org/historic-trends-in-chess-ai/), 2006 is the year when the highest machine Elo rating surpassed the highest human Elo (both the highest at the time, and the highest in 2020). In particular Rybka 1.2 was rated 2902. At the time, the highest human Elo rating was Garry Kasparov at 2851.[9](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-9-2673 "“Comparison of Top Chess Players throughout History.” In Wikipedia, July 27, 2020. https://en.wikipedia.org/w/index.php?title=Comparison_of_top_chess_players_throughout_history&oldid=969714742.")
Thus it took around 49 years for computers to progress from beginner human level chess to superhuman chess.

#### Pre-human range

The Chess Programming Wiki says that the 1957 Bernstein Chess program was the first complete chess program.[10](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-10-2673 "“The Bernstein Chess Program,
was the first complete chess program, developed around 1957“

“The Bernstein Chess Program.” In Chess Programming WIKI. Accessed October 13, 2020. https://www.chessprogramming.org/The_Bernstein_Chess_Program.") This seems likely to be the same Bernstein program noted by Moravec as having an 800 Elo in 1957 (see above). Thus if correct, this means that once machines could complete the task of playing chess at all, they could already do it at human beginner level. This may not be accurate (none of these sources appear to be very reliable), but it strongly suggests that the time between lowest possible performance and beginner human performance was not as long as decades.

#### Superhuman performance range

The Swedish Chess Computer Association has measured continued progress. As of July 2020, the best chess machine is rated 3558[11](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-11-2673 "“The SSDF Rating List.” Accessed October 15, 2020. https://ssdf.bosjo.net/list.htm."), whereas in 2019 sometime, the highest rating was 3529.[12](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-12-2673 "“Swedish Chess Computer Association.” In Wikipedia, September 19, 2020. https://en.wikipedia.org/w/index.php?title=Swedish_Chess_Computer_Association&oldid=979229545.") Alphazero also appeared to have an Elo just below 3500 in 2017, according to its creators (from a small figure with unclear labels).[13](https://aiimpacts.org/time-for-ai-to-cross-the-human-performance-range-in-chess/#easy-footnote-bottom-13-2673 "See Figure 1:

Silver, David, Thomas Hubert, Julian Schrittwieser, Ioannis Antonoglou, Matthew Lai, Arthur Guez, Marc Lanctot, et al. “Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm.” ArXiv:1712.01815 [Cs], December 5, 2017. http://arxiv.org/abs/1712.01815.")

We know of no particular upper bound to chess performance.

This suggests that so far the superhuman range in chess playing has permitted at least least 14 years of further progress, and may permit much more.

***Primary author: Katja Grace***

Notes
-----