Valliappa Lakshmanan National Severe Storms Laboratory & University of Oklahoma Norman, OK, USA lakshman@ou.edu Geneva Center for Security Policy May 6, 2011

ARTIFICIAL INTELLIGENCE: ENVIRONMENTAL IMPLICATIONS

AI Environmental Implications • AI is mostly a force for good in terms of the environment

• But there are issues that the prevalence of AI brings about

Hazardous situations • Robots useful in situations where you can’t send humans

• Example: in the aftermath of the Japan March 2011 earthquake

Mike Fein/ BLOOMBERG

Impossible environments • Robots used in the June 2010 Gulf of Mexico oil cleanup

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A remotely operated vehicle used to place dome over gushing oil well.

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Unmanned underwater vehicle used to track hydrocarbons after spill

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Monitoring out-of-the-way places • Remotely managed automated monitoring instruments

• Maintenance a major obstacle, cost sink

• Active area of research: self-correction

NOAA

Oklahoma Climate Survey

Machine Intelligence • Most uses of AI in the environmental sciences is as software

• For making sense of observed and modeled data

Burrows, 2009 WDSS-II WDSS-II

NSSL Waugh, NSSL

Warnings updated more frequently

Stumpf, 2011

Earlier, more accurate warnings • EF-4 tornado through the heart of Enterprise, Alabama in 2007

NOAA 2007 NOAA 2007

Man-in-loop to man-over-loop • After Alabama outbreak, April 2011

Photo: James LaDue, NOAA

Deploying oil skimmers • Models can predict spread of oil slick

Klemas 2010

Efficient manufacture and less waste • Fewer defects in manufactured products

• Less waste. improves environment

Gordon Hodgson

truthaboutcars RedBus2US

Jevon’s paradox

Source: Wikipedia

By Arby Reed

Impact of earlier warnings

Hoekstra et al., 2009 From Travelbrook

Makes dubious projects possible

CNN

Brenntag

Applicable to hazardous wastes? • Robots make wider range of economic activity possible

• If humans had to build and maintain deep-sea wells, we may not have any

• Does robot cleanup embolden regulators and businesses?

Robot accidents • Increased prevalence of robots and automated instruments leads to

cross-contamination and accidents

• Typically, robots are designed for pristine environments

• Have problems in the presence of robots from different manufacturers or in the presence of humans who behave unpredictably

Extreme event forecasting skills suffer • Machine intelligence good at predicting statistically likely events

• Over time, humans start to let computers make decisions

• Fails during extreme events, exactly when forecasts are most critical

Roger Edwards, SPC

Summary • AI in the environment is mostly a force for good

• Robots can operate in hazardous situations

• Automated instruments can be placed in remote places

• Can lead to earlier, more accurate warnings

• Issues

• Jevon’s paradox may lead to increased incidence of hazardous cleanup

• Population often starts to expect increased lead time, negating advances

• Robot accidents more likely because of multi-vendor robots

• Extreme event forecasting skills start to suffer

Thanks to GCSP for the hospitality and for organizing a very interesting workshop!