Artificial Intelligence: Environment Implications -...
Transcript of Artificial Intelligence: Environment Implications -...
Valliappa Lakshmanan National Severe Storms Laboratory & University of Oklahoma Norman, OK, USA [email protected] 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
Earlier, more accurate warnings • EF-4 tornado through the heart of Enterprise, Alabama in 2007
NOAA 2007 NOAA 2007
Efficient manufacture and less waste • Fewer defects in manufactured products
• Less waste. improves environment
Gordon Hodgson
truthaboutcars RedBus2US
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!