Collaborating Authors


AI to help organizations cut greenhouse gas emissions by 16%


The potential positive impact of Artificial Intelligence (AI) is significant and organizations can expect to cut GHG emissions by 16% in the next three to five years through AI-driven climate action projects according to a research report by Capgemini Research Institute. Despite the considerable potential of AI for climate action, adoption remains low. More than eight in ten organizations spend less than 5% of climate change investment on AI and data tracking; 54% have fewer than 5% of employees with the skills to take up data and AI-driven roles; and more than a third (37%) of sustainability executives have decelerated their climate goals in light of COVID-19, with the highest deceleration in the energy and utilities industry. Only 13% of organizations have aligned their climate vision and strategy with their AI capabilities – these are who Capgemini defines as climate AI champions. Two-fifths of these come from Europe, followed by the Americas and APAC.

Can Artificial Intelligence Save the Regulatory State?


The Department of Justice recently sued Google for allegedly monopolizing the market for search engines. The Department's complaint alleges that Google took numerous actions well before 2010 that formed part of the claimed antitrust violations. I have no comment about the merits. What I do want to call attention to, however, are the dates: a lawsuit beginning in 2020 to try to correct the market consequences of actions that began more than 10 years ago. The revolution that some scholars call "regulating by robot" is already underway.

AI Invents Ways to Protect Nuclear Waste Sites - Nerdist


OpenAI's new immensely convincing language generator, GPT-3, recently demonstrated its rhetorical prowess when it argued the case for why it's harmless. Now, research scientist Janelle Shane has used the tool to generate something a bit more lighthearted. Namely, ideas on how to make nuclear waste sites safe for thousands upon thousands of years. Are you not terrified and repulsed?? I prompted GPT-3 with some human proposals for marking a nuclear waste site, in a way that will still be forbidding millennia from now.

How ensembles can reduce machine learning's carbon footprint - Dataconomy


Commercial and industrial applications of artificial intelligence and machine learning are unlocking economic opportunities, transforming the way we do business, and even helping to solve complex social and environmental problems. In fact, generative applications of this technology have become tools for environmental sustainability. With machine learning's capability to analyze and make predictions using massive pools of data, these applications are now able to accurately model climate change and fluctuations, so that energy infrastructures and energy consumption can be re-engineered accordingly. Ironically, training large-scale models via deep neural networks requires vast computational power. It also produces a great deal of thermal energy from each of the associated graphics processing units (GPUs) or tensor processing units (TPUs) used.

Engage with animal welfare in conservation


Leading conservationists have emphasized that conservation's priority is the protection of species and populations, not the welfare of individual nonhuman animals (hereafter “animals”) ([ 1 ][1]–[ 3 ][2]). Although individual conservationists often harbor concern for animal welfare, conservation organizations and scientists frequently downplay or ignore the ethical implications of actions they promote that harm individual animals, from culling and sport hunting to the discontinuation of wildlife rescue from oil spills ([ 3 ][2]–[ 5 ][3]). A growing body of scientific evidence should prompt conservation organizations to reconsider their inattention to animal welfare. A wide variety of vertebrate species (and perhaps some invertebrates) are capable of experiencing physical and emotional pain, engaging in substantive relationships, and executing cognitively complex tasks ([ 6 ][4]–[ 8 ][5]), bolstering claims that animal well-being is morally significant and policy-relevant. Addressing animal welfare in conservation would be politically challenging, and given the central role of predation and competition in ecosystems, conservation science cannot altogether avoid difficult decisions; harming animals can be a necessary step toward a worthwhile goal. Despite these trade-offs, conservation organizations face a singular opportunity to reshape conservation into a discipline that promotes both the quantity of species and the quality of animal life. Although humans are exceptional in many ways, the once-popular belief that it is unscientific to ascribe emotions or thoughts to animals is now regarded as inconsistent with evolutionary theory, experimental evidence, and any reasonable burden of proof ([ 9 ][6], [ 10 ][7]). Commonalities in basic neural functioning across vertebrate species, ranging from fish to mammals, suggest similarities in experiential capacities ([ 9 ][6], [ 11 ][8]). Evidence indicates that the thalamocingulate division of the limbic system and the anterior cingulate cortex evolved prior to the radiation of mammals, with all studied mammals sharing seven basic emotional systems including joy, fear, grief, parental nurturance, and playfulness. Deep neurological similarities underpin the extensive use of mammalian models in medical research, including for depression and anxiety. Further, research indicates that convergent evolution of the mammalian cortex and avian pallium has led to similar neural architecture between birds and mammals ([ 12 ][9]), with birds exhibiting similar forms of some affective states, consciousness, and attachment-oriented behaviors. Recent research has also demonstrated that various animal species are cognitively sophisticated, with findings including tool use in diverse taxa; spontaneous insight and innovative behavior; self-recognition and metacognition; collaboration to solve unfamiliar tasks; planning for future events; political strategy; empathetic concern; and the ability to recognize hundreds of human words (see supplementary materials). The accumulating scientific evidence that animals have vibrant inner lives was anticipated by modern philosophers, the field of animal welfare science, and numerous world cultures that have accorded moral relevance to the quality of animal life. Yet with limited exceptions, the most prominent international conservation organizations do not attempt to promote animal welfare in their mission or vision statements or to safeguard animal welfare in their readily available public policies. This contrasts with often robust ethics policies on a range of other social and environmental issues. From one perspective, the omission of animal welfare is befuddling. Conservationists must believe that animals deserve protection from human-induced harm; by combating habitat destruction and poaching, conservation often already promotes wild animal welfare. Officially recognizing the imperative of protecting animals as individuals could broaden conservation's constituency. Whereas the public often finds the value of biodiversity to be abstract and unrelatable, many people are concerned when human actions unnecessarily violate the freedom and well-being of wild animals. Conservation organizations have realized this, often using stories of human-induced suffering of individual animals to generate empathy and raise funds. Yet, owing to the pervasiveness of activities that compromise animal welfare, many conservation organizations could face a variety of political risks and programmatic complications if they were to officially endorse the legitimacy of animal welfare concerns. Conservation organizations often depend on a diverse coalition of political interests, including groups that habitually harm animals. For instance, the U.S. government is one of the largest bilateral sources of funding for international conservation largely because the U.S. Congress's International Conservation Caucus is among the largest bipartisan caucuses in the legislature, with many participants being vocal supporters of recreational hunting and fishing. For conservation organizations to acknowledge that killing animals for recreation might have moral implications ([ 4 ][10]) could complicate these politically important relationships in both halls of power and remote settings globally. There are well-evidenced concerns for how wild animals, especially wide-ranging species like elephants, some cetaceans, and carnivores, fare in captivity, but zoos can also inspire considerable support for wildlife conservation. Finally, conservation organizations and conservationists themselves (like other environmentalists) often regularly purchase factory farm products even though factory farms pose serious concerns about human-induced animal suffering. For conservation organizations, officially acknowledging the moral significance of animal welfare could complicate how many conservationists see themselves and generally cause discontent within their communities. Furthermore, conservation programming takes place in complex socioecological systems that pose practical trade-offs between animal welfare and biodiversity conservation or even human rights. At its extreme, efforts to curtail hunting and fishing in the world's poor rural areas could unjustly harm communities that rely on bushmeat or wild fish for their nutrition and livelihoods. Conservation groups can be seen as elitist, out-of-touch, or culturally oppressive where they oppose the killing of dangerous animals like elephants or traditional practices like subsistence whaling—such conflicts could become more common if conservation organizations consistently prioritize the interests of individual animals. In settings where wildlife tourism is not profitable, prohibiting sport hunting could deprive organizations of funding to protect wildlife from poaching, perversely leading to an increase in the killing of wildlife. Additionally, there are many examples of direct trade-offs between animal welfare and traditional conservation objectives like preventing extinction and maintaining ecosystem function. Invasive mammals—like goats on the Galapagos or feral cats on remote islands—suffer during eradication campaigns, but there may be no other way to secure the future for endangered native species. Programs to cull white-tailed deer similarly might be necessary to ensure the regeneration of forests in the eastern United States. Ecological research and reintroduction programs can also involve duress for the animals involved. Despite challenges posed by these trade-offs, conservation science should adjust its priorities in response to the overwhelming evidence that animals think and feel. Only explicit consideration of animal welfare in decision-making can ensure that conservation organizations do not unnecessarily compromise the well-being of individual animals. As a community, conservation organizations should set in motion three processes to (i) develop consensus principles, (ii) build the evidence base to identify best practices, and (iii) develop advisory institutions that can advance best practices. Each of these should engage diverse voices, including representatives from different cultures, countries with diverse political realities, and researchers and practitioners from both animal welfare science and conservation. The process of developing consensus principles to bring animal welfare concerns into conservation science has already begun, with ideas coming from national regulatory bodies, nongovernmental organizations concerned with wild animal welfare, the World Association of Zoos and Aquariums ([ 13 ][11]), animal welfare experts ([ 14 ][12], [ 15 ][13]), and the burgeoning compassionate conservation movement ([ 3 ][2], [ 4 ][10]). Conservation and animal welfare organizations should collaborate to systematically refine and select practically applicable ethical principles. Given the diverse cultural practices and economic systems that involve harm to animals, prohibitions on animal captivity, killing animals, and eating meat are unlikely to gain consensus support—but that need not prevent constructive discussions on minimizing human-induced suffering of animals, general agreement to minimize suffering during killing, and principles guiding the circumstances when killing animals might be acceptable. Animal welfare principles can alert conservationists to when the harm an activity causes to individual animals outweighs the benefits to biodiversity. Second, international conservation and animal welfare organizations should fund the development of an evidence base for how best to engage with wildlife in a way that minimizes avoidable suffering. Again, scientists have begun this process ([ 4 ][10], [ 13 ][11], [ 14 ][12])—but the evidence compiled must come from more diverse settings and situations and reflect practical limitations and trade-offs faced by conservation organizations in places where even human rights are not adequately realized. In addition to improving conservation practice, such evidence would help animal welfare organizations recognize where the protection of biodiversity, ecological function, and local communities might necessitate harming individual animals. This evidence review process would also highlight areas of research that could help resolve ethical dilemmas posed by conservation programming. International conservation bodies should also work with animal welfare scientists to establish advisory committees that review (voluntarily submitted) conservation project proposals to assess whether they satisfy principles of animal welfare. The process could be modeled as a voluntary version of the Institutional Animal Care and Use Committee that reviews animal research in the United States, working to promote best practices, build precedent, and collect real-life cases that can improve the evidence base. The committees' recommendations should provide a basis for informed debate about the trade-offs between wildlife conservation and animal welfare, helping better define whether the suffering of individual animals might be commensurate with conservation benefits ([ 14 ][12]). Over time, the cumulative experience of these committees should allow conservation organizations to recommend evidence-based animal welfare safeguards that can fit into the broader category of social and environmental safeguards, much like policies striving to minimize carbon emissions or protect human rights in conservation and development. Inevitably, these processes will take time. In the meanwhile, conservation organizations can take two steps toward building a better world for all animals: publicly commit to considering animal welfare in their decisions, and adopt policies against the purchase of factory farm meat where less harmful alternatives are available. Given the implications of factory farming not just for animal welfare but also for climate change and biodiversity, such action would further demonstrate the sincerity of conservation organizations' pursuit of a more just and sustainable planet. [][14] 1. [↵][15]1. M. E. Soule , Bioscience 35, 727 (1985). [OpenUrl][16][CrossRef][17][Web of Science][18] 2. 1. P. Kareiva, 2. M. Marvier , Bioscience 62, 962 (2012). [OpenUrl][19][CrossRef][20][Web of Science][21] 3. [↵][22]1. D. Ramp, 2. M. Bekoff , Bioscience 65, 323 (2015). [OpenUrl][23][CrossRef][24] 4. [↵][25]1. A. D. Wallach et al ., Conserv. Biol. 32, 1255 (2018). [OpenUrl][26] 5. [↵][27]1. P. Kareiva, 2. M. Marvier, 3. B. Silliman 1. J. A. Estes, 2. M. T. Tinker , in Effective Conservation Science: Data Not Dogma, P. Kareiva, M. Marvier, B. Silliman, Eds. (Oxford Univ. Press, 2017), pp. 128–134. 6. [↵][28]1. V. A. Braithwaite, 2. P. Boulcott , Dis. Aquat. Organ. 75, 131 (2007). [OpenUrl][29][PubMed][30] 7. 1. I. B.-A. Bartal et al ., Science 334, 1427 (2011). [OpenUrl][31][Abstract/FREE Full Text][32] 8. [↵][33]1. N. S. Clayton, 2. A. Dickinson , Nature 395, 272 (1998). [OpenUrl][34][CrossRef][35][PubMed][36][Web of Science][37] 9. [↵][38]1. J. Panksepp , PLOS ONE 6, e21236 (2011). [OpenUrl][39][CrossRef][40][PubMed][41] 10. [↵][42]1. G. A. Mashour, 2. M. T. Alkire , Proc. Natl. Acad. Sci. U.S.A. 110 (suppl.2), 10357 (2013). [OpenUrl][43][Abstract/FREE Full Text][44] 11. [↵][45]1. T. E. Feinberg, 2. J. Mallatt , Front. Psychol. 4, 667 (2013). [OpenUrl][46][PubMed][47] 12. [↵][48]1. A. B. Butler, 2. R. M. J. Cotterill , Biol. Bull. 211, 106 (2006). [OpenUrl][49][CrossRef][50][PubMed][51][Web of Science][52] 13. [↵][53]1. D. J. Mellor et al ., Caring for Wildlife: The World Zoo and Aquarium Animal Welfare Strategy (WAZA Executive Office, 2015). 14. [↵][54]1. S. Dubois et al ., Conserv. Biol. 31, 753 (2017). [OpenUrl][55] 15. [↵][56]1. J. O. Hampton et al ., Conserv. Biol. 33, 751 (2019). [OpenUrl][57] Acknowledgments: We thank H. Telkänranta, N. Shah, S. Sekar, N. Mohapatra, D. Mistree, M.Malik, A.Lerner, K. Kolappa, S. Kishore, P. Hannam, G. Fricchione, M. Doshi, P. Chanchani, and four anonymous reviewers. This piece reflects the views of the authors and not the official positions of their organizations. 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Artificial Intelligence and Satellite Technology to Enhance Carbon Tracking Measures


New carbon emission tracking technology will quantify emissions of greenhouse gas, holding the energy industry accountable for its CO2 output. Backed by Google, this cutting-edge initiative will be known as Climate TRACE (Tracking Real-Time Atmospheric Carbon Emissions). Advanced AI and machine learning now make it possible to trace greenhouse gas (GHG) emissions from factories, power plants and more. By using image processing algorithms to detect carbon emissions from power plants, AI technology makes use of the growing global satellite network to develop a more comprehensive global database of power plant activity. Because most countries self-report emissions and manually compile results, scientists often rely on data that is several years out of date.

Council Post: In EU's Climate Change Fight, The 2 Trillion Euros Was The Easy Part


Bureaucrats -- particularly those from the European Union (EU) -- rarely get the praise they deserve. By their nature, they are reserved, so they do not draw attention to themselves when things go well. When things go poorly, though, they make for a convenient target. So when the EU does something bold, we should give it its due. The EU's boldness in addressing a host of environmental problems head-on is unmatched.

A robot sloth will (very slowly) survey endangered species


Most animal-inspired robots are designed to move quickly, but Georgia Tech's latest is just the opposite. Their newly developed SlothBot is built to study animals, plants and the overall environment below them by moving as little as possible. It inches along overhead cables only when necessary, charging itself with solar panels to monitor factors like carbon dioxide levels and weather for as long as possible -- possibly for years. It even crawls toward the sunlight to ensure it stays charged. The 3D-printed shell helps SlothBot blend in (at least in areas where sloths live) while sheltering its equipment from the rain.

How to reverse-engineer a rainforest


But 2019 was the year the earth burned. In Australia, the world watched in horror as bushfires destroyed 10.3 million hectares, marking the continent's most intense and destructive fire season in over 40 years. Earlier that fall, California saw more than 101,000 hectares destroyed, with damages upward of $80 billion. Alaska saw nearly a million. Record-breaking fires also hit Indonesia, Russia, Lebanon -- but nowhere saw the sheer mass of media coverage as the fires that tore through the Amazon nearly all last summer. By year's end, thousands of global media outlets had reported that Brazil's largest rainforest played host to more than 80,000 individual forest fires in 2019, resulting in an estimated 906,000 square hectares of environmental destruction. At the time, Brazil's National Institute for Space Research reported it was the fastest rate of burning since record keeping began in 2013. But amid the charred ruins of one of the largest oxygen-producing environments on the planet, a secret lies buried beneath the soil.

Deep Neural Network Based Ambient Airflow Control through Spatial Learning


As global energy regulations are strengthened, improving energy efficiency while maintaining performance of electronic appliances is becoming more important. Especially in air conditioning, energy efficiency can be maximized by adaptively controlling the airflow based on detected human locations; however, several limitations such as detection areas, the installation environment, and sensor quantity and real-time performance which come from the constraints in the embedded system make it a challenging problem. In this study, by using a low resolution cost effective vision sensor, the environmental information of living spaces and the real-time locations of humans are learned through a deep learning algorithm to identify the living area from the entire indoor space. Based on this information, we improve the performance and the energy efficiency of air conditioner by smartly controlling the airflow on the identified living area. In experiments, our deep learning based spatial classification algorithm shows error less than 5 .