scholarly journals Black boxes, not green: Mythologizing artificial intelligence and omitting the environment

2020 ◽  
Vol 7 (2) ◽  
pp. 205395172093514 ◽  
Author(s):  
Benedetta Brevini
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Chronic Diseases ◽  
Public Discourse ◽  
Traffic Accidents ◽  
Data Centers ◽  
Environmental Problems ◽  
Environmental Costs ◽  
Scarce Resources ◽  
Black Boxes

We are repeatedly told that AI will help us to solve some of the world's biggest challenges, from treating chronic diseases and reducing fatality rates in traffic accidents to fighting climate change and anticipating cybersecurity threats. However, the article contends that public discourse on AI systematically avoids considering AI’s environmental costs. Artificial Intelligence- Brevini argues- runs on technology, machines, and infrastructures that deplete scarce resources in their production, consumption, and disposal, thus increasing the amounts of energy in their use, and exacerbate problems of waste and pollution. It also relies on data centers, that demands impressive amounts of energy to compute, analyse, categorize. If we want to stand a chance at tackling the Climate Emergency, then we have to stop avoiding addressing the environmental problems generated by AI.

scholarly journals Anxiety, Worry, and Grief in a Time of Environmental and Climate Crisis: A Narrative Review

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
Maria Ojala ◽  
Ashlee Cunsolo ◽  
Charles A. Ogunbode ◽  
Jacqueline Middleton
Keyword(s):  
Climate Change ◽  
Public Discourse ◽  
Negative Emotions ◽  
Well Being ◽  
Environmental Problems ◽  
Narrative Review ◽  
Annual Review ◽  
Publication Date ◽  
The One ◽  
Climate Crisis

Climate change worry, eco-anxiety, and ecological grief are concepts that have emerged in the media, public discourse, and research in recent years. However, there is not much literature examining and summarizing the ways in which these emotions are expressed, to what processes they are related, and how they are distributed. This narrative review aims to ( a) summarize research about the relationships between, on the one hand, negative emotions in relation to climate change and other environmental problems and, on the other hand, mental well-being among people in different parts of the world and ( b) examine studies that have explored the potentially constructive role of worry—for example, in the form of providing motivation to act. It is clear from this review that negative emotions regarding environmental problems are normal, and often constructive, responses. Yet, given the nature, range, and extent of these emotions, it is important to identify diverse place-based and culturally relevant strategies to help people cope. Expected final online publication date for the Annual Review of Environment and Resources, Volume 46 is October 2021. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Machine Learning in Agriculture

2018 ◽  
Vol 8 (6) ◽  
pp. 26 ◽  
Author(s):  
Matthew N. O. Sadiku ◽  
Chandra M. M Kotteti ◽  
Sarhan M. Musa
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Disease Diagnosis ◽  
Automated Detection ◽  
Disease Prediction ◽  
Paper Briefly ◽  
Agriculture Sector ◽  
Modern Agriculture ◽  
Crop Disease

Machine learning is an emerging field of artificial intelligence which can be applied to the agriculture sector. It refers to the automated detection of meaningful patterns in a given data.  Modern agriculture seeks ways to conserve water, use nutrients and energy more efficiently, and adapt to climate change.  Machine learning in agriculture allows for more accurate disease diagnosis and crop disease prediction. This paper briefly introduces what machine learning can do in the agriculture sector.

Political Preferences, Personality Traits, and Environmentalism

2020 ◽  
Author(s):  
Alistair Soutter ◽  
René Mõttus
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
Personality Traits ◽  
Public Discourse ◽  
Environmental Attitudes ◽  
Scientific Evidence ◽  
Political Orientation ◽  
Anthropogenic Climate Change ◽  
Political Preferences ◽  
Party Voting

Although the scientific evidence of anthropogenic climate change continues to grow, public discourse still reflects a high level of scepticism and political polarisation towards anthropogenic climate change. In this study (N = 499) we attempted to replicate and expand upon an earlier finding that environmental terminology (“climate change” versus “global warming”) could partly explain political polarisation in environmental scepticism (Schuldt, Konrath, & Schwarz, 2011). Participants completed a series of online questionnaires assessing personality traits, political preferences, belief in environmental phenomenon, and various pro-environmental attitudes and behaviours. Those with a Conservative political orientation and/or party voting believed less in both climate change and global warming compared to those with a Liberal orientation and/or party voting. Furthermore, there was an interaction between continuously measured political orientation, but not party voting, and question wording on beliefs in environmental phenomena. Personality traits did not confound these effects. Furthermore, continuously measured political orientation was associated with pro-environmental attitudes, after controlling for personality traits, age, gender, area lived in, income, and education. The personality domains of Openness, and Conscientiousness, were consistently associated with pro-environmental attitudes and behaviours, whereas Agreeableness was associated with pro-environmental attitudes but not with behaviours. This study highlights the importance of examining personality traits and political preferences together and suggests ways in which policy interventions can best be optimised to account for these individual differences.

scholarly journals Public perceptions of Lyme disease and climate change in southern Manitoba, Canada: making a case for strategic decoupling of climate and health messages

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Laura Cameron ◽  
Rhéa Rocque ◽  
Kailey Penner ◽  
Ian Mauro
Keyword(s):  
Public Health ◽  
Climate Change ◽  
Risk Perception ◽  
Lyme Disease ◽  
Risk Perceptions ◽  
Public Discourse ◽  
Behavioural Change ◽  
Health Messages ◽  
Urban Rural ◽  
Climate And Health

Abstract Background Despite scientific evidence that climate change has profound and far reaching implications for public health, translating this knowledge in a manner that supports citizen engagement, applied decision-making, and behavioural change can be challenging. This is especially true for complex vector-borne zoonotic diseases such as Lyme disease, a tick-borne disease which is increasing in range and impact across Canada and internationally in large part due to climate change. This exploratory research aims to better understand public risk perceptions of climate change and Lyme disease in order to increase engagement and motivate behavioural change. Methods A focus group study involving 61 participants was conducted in three communities in the Canadian Prairie province of Manitoba in 2019. Focus groups were segmented by urban, rural, and urban-rural geographies, and between participants with high and low levels of self-reported concern regarding climate change. Results Findings indicate a broad range of knowledge and risk perceptions on both climate change and Lyme disease, which seem to reflect the controversy and complexity of both issues in the larger public discourse. Participants in high climate concern groups were found to have greater climate change knowledge, higher perception of risk, and less skepticism than those in low concern groups. Participants outside of the urban centre were found to have more familiarity with ticks, Lyme disease, and preventative behaviours, identifying differential sources of resilience and vulnerability. Risk perceptions of climate change and Lyme disease were found to vary independently rather than correlate, meaning that high climate change risk perception did not necessarily indicate high Lyme disease risk perception and vice versa. Conclusions This research contributes to the growing literature framing climate change as a public health issue, and suggests that in certain cases climate and health messages might be framed in a way that strategically decouples the issue when addressing climate skeptical audiences. A model showing the potential relationship between Lyme disease and climate change perceptions is proposed, and implications for engagement on climate change health impacts are discussed.

scholarly journals Artificial Intelligence and Behavioral Science Through the Looking Glass: Challenges for Real-World Application

2020 ◽  
Vol 54 (12) ◽  
pp. 942-947
Author(s):  
Pol Mac Aonghusa ◽  
Susan Michie
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Machine Learning ◽  
Behavior Change ◽  
Behavioral Science ◽  
Lessons Learned ◽  
Learning Approaches ◽  
Intervention Evaluation ◽  
Research Activities ◽  
Behavior Change Interventions

Abstract Background Artificial Intelligence (AI) is transforming the process of scientific research. AI, coupled with availability of large datasets and increasing computational power, is accelerating progress in areas such as genetics, climate change and astronomy [NeurIPS 2019 Workshop Tackling Climate Change with Machine Learning, Vancouver, Canada; Hausen R, Robertson BE. Morpheus: A deep learning framework for the pixel-level analysis of astronomical image data. Astrophys J Suppl Ser. 2020;248:20; Dias R, Torkamani A. AI in clinical and genomic diagnostics. Genome Med. 2019;11:70.]. The application of AI in behavioral science is still in its infancy and realizing the promise of AI requires adapting current practices. Purposes By using AI to synthesize and interpret behavior change intervention evaluation report findings at a scale beyond human capability, the HBCP seeks to improve the efficiency and effectiveness of research activities. We explore challenges facing AI adoption in behavioral science through the lens of lessons learned during the Human Behaviour-Change Project (HBCP). Methods The project used an iterative cycle of development and testing of AI algorithms. Using a corpus of published research reports of randomized controlled trials of behavioral interventions, behavioral science experts annotated occurrences of interventions and outcomes. AI algorithms were trained to recognize natural language patterns associated with interventions and outcomes from the expert human annotations. Once trained, the AI algorithms were used to predict outcomes for interventions that were checked by behavioral scientists. Results Intervention reports contain many items of information needing to be extracted and these are expressed in hugely variable and idiosyncratic language used in research reports to convey information makes developing algorithms to extract all the information with near perfect accuracy impractical. However, statistical matching algorithms combined with advanced machine learning approaches created reasonably accurate outcome predictions from incomplete data. Conclusions AI holds promise for achieving the goal of predicting outcomes of behavior change interventions, based on information that is automatically extracted from intervention evaluation reports. This information can be used to train knowledge systems using machine learning and reasoning algorithms.

scholarly journals Climate Change Inaction and Optimism

Philosophies ◽  
2021 ◽  
Vol 6 (3) ◽  
pp. 61
Author(s):  
Philip J. Wilson
Keyword(s):  
Climate Change ◽  
Economic Growth ◽  
Collective Action ◽  
Public Discourse ◽  
Collective Action Problem ◽  
The Public ◽  
Policy Context ◽  
Positive Action ◽  
Ideological Fantasy

The problem of climate change inaction is sometimes said to be ‘wicked’, or essentially insoluble, and it has also been seen as a collective action problem, which is correct but inconsequential. In the absence of progress, much is made of various frailties of the public, hence the need for an optimistic tone in public discourse to overcome fatalism and encourage positive action. This argument is immaterial without meaningful action in the first place, and to favour what amounts to the suppression of truth over intellectual openness is in any case disreputable. ‘Optimism’ is also vexed in this context, often having been opposed to the sombre mood of environmentalists by advocates of economic growth. The greater mental impediments are ideological fantasy, which is blind to the contradictions in public discourse, and the misapprehension that if optimism is appropriate in one social or policy context it must be appropriate in others. Optimism, far from spurring climate change action, fosters inaction.

scholarly journals Using Artificial Intelligence to Visualize the Impacts of Climate Change

2021 ◽  
Vol 41 (1) ◽  
pp. 8-14
Author(s):  
Alexandra Luccioni ◽  
Victor Schmidt ◽  
Vahe Vardanyan ◽  
Yoshua Bengio ◽  
Theresa-Marie Rhyne
Keyword(s):  
Climate Change ◽  
Artificial Intelligence ◽  
Impacts Of Climate Change

scholarly journals The widespread collapse of an invasive species: Argentine ants ( Linepithema humile ) in New Zealand

2011 ◽  
Vol 8 (3) ◽  
pp. 430-433 ◽  
Author(s):  
Meghan Cooling ◽  
Stephen Hartley ◽  
Dalice A. Sim ◽  
Philip J. Lester
Keyword(s):  
Climate Change ◽  
Invasive Species ◽  
New Zealand ◽  
Argentine Ant ◽  
Environmental Costs ◽  
Argentine Ants ◽  
Ant Communities ◽  
Mean Survival Time ◽  
Colony Collapse ◽  
Increasing Temperature

Synergies between invasive species and climate change are widely considered to be a major biodiversity threat. However, invasive species are also hypothesized to be susceptible to population collapse, as we demonstrate for a globally important invasive species in New Zealand. We observed Argentine ant populations to have collapsed in 40 per cent of surveyed sites. Populations had a mean survival time of 14.1 years (95% CI = 12.9–15.3 years). Resident ant communities had recovered or partly recovered after their collapse. Our models suggest that climate change will delay colony collapse, as increasing temperature and decreasing rainfall significantly increased their longevity, but only by a few years. Economic and environmental costs of invasive species may be small if populations collapse on their own accord.

ANALYSIS OF THE RELATIONSHIP BETWEEN CLIMATE CHANGE AND PATTERNS OF FARMERS’/PASTORALISTS’ CONFLICTS IN ZAMFARA STATE, NIGERIA

2021 ◽  
Vol 4 (4) ◽  
pp. 56-66
Author(s):  
Olasunkanmi Gabriel Jeje ◽  
B. A. Sawa ◽  
Y. A. Arigbede
Keyword(s):  
Climate Change ◽  
Rating Scale ◽  
Implementation Framework ◽  
Scarce Resources ◽  
Purposeful Sampling ◽  
Climate Change Information ◽  
Study Results ◽  
Ranch Management ◽  
Key Informant Interview ◽  
The Relationship

Struggle over land and scarce resources have resulted in perennial and growing violent conflicts amongst arable crop farmers and cattle herdsmen in various parts of Nigeria. This study analyses the relationship between climate change and patterns of herders-crop farmers’ conflict in Zamfara state, Nigeria. Data for this study were acquired via semi structured questionnaire and Key Informant Interview. Purposeful sampling method was used to select six communities, while 260 farmers and 67 pastoralists were chosen as sample size for the survey based on Krejcie and Morgan’s formula. Descriptive statistics such as percentages, arithmetic mean and Likert rating scale were adopted to analyze the data for the study. Results from the findings indicated that farmers and herders in Zamfara state were within active years of economic and productive age (24 to 44 years). Nearly,75% of both farmers and pastoralists in the study communities professed there is high variability in rainfall pattern  and increase in temperature. Three-quarter of the respondents confirmed that the nature of the conflicts was assault involving the use of arms; whereas two-fifth of the respondents affirmed that the conflict occurs during harvest and the planting seasons.  The study concluded that climate change is the bane of incessant resource use conflicts in the study area. Thus a clearly formulated government policies and implementation framework that would boost climate change information forecasting and dissemination, adaptive capacity and ranch management will salvage the conflictual relationship subsisting between farmers and herders in the study area

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