Artificial intelligence (AI) and cleantech adoption are largely considered to be one-and-the-same these days. AI is compressing and analyzing the massive amounts of data that the cleantech industry produces. It can help optimize solar and wind farms, simulate climate and weather, enhance power grid reliability and resilience, and advance carbon capture and power fusion breakthroughs. Its original prophecy to improve efficiency, reduce costs, and speed up R&D has been proven. However, ethical AI concerns do haunt the cleantech industry.
Do AI’s multi-layered cleantech systems contain nearly impossible-to-detect mechanisms that discriminate and divide at scale?
Will cleantech companies infuse transparency so that the total amount of AI power and emissions they use is revealed?
How is cleantech designing ethical AI algorithmic decision-making so objectivity is built into methodology?
Will cleantech companies address ethical AI issues, possibly as part of their ESG framework?
With new mandates to reduce climate pollution, manufacturers and other commercial enterprises are implementing clean technologies in order to optimize their operations. Recent advances in AI offer the promise of massive benefits to society, and, together, AI and cleantech are securing breakthroughs in how we produce, store, and consume energy. As national energy mixes become more differentiated to accommodate renewables, integrating and managing these different energy sources becomes more complex.
With cleantech, the aim is to utilize alternative sources of energy such as wind, solar, and hydroelectric energy to supply the utilities that fossil fuels have provided in the past. Whether using traditional AI (which focuses on performing a specific task intelligently) or generative AI (which can create text outputs, images, music, and computer code), cleantech has the capacity to provide revelatory solutions to the climate crisis.
For example, AI is changing the way we convert and dispose of our waste. It is helping utilities and energy companies monitor the integrity of pipelines, allowing for predictive maintenance and preventing hazardous incidents. It is becoming a central element of urban planning, where city planners can combine growth projections with future trends in water availability to optimize all investment in infrastructure for maximum effect. It may hold the key to maximizing the effectiveness of integrated monitoring/smart metering of water systems. AI can analyze wildfire potential and assist with better grids. And we can’t forget autonomous vehicles, where AI cleantech is showing possibilities so that fleets of self-driving trucks can be tasked with wholly optimized collection routes.
Cleantech startups are also making crucial advances in reducing adverse environmental impacts, and many new cleantech companies use AI as an integral part of their performance. Shayp uses machine learning and real-time data to report when water is unnecessarily wasted due to leakages or system discrepancies in buildings. Recycleye uses advanced machine learning, computer vision, and robotics to commodify waste. Glint Solar builds solar screening and analysis software that uses satellite data to identify and analyze thousands of potential solar project sites in a given region.
Innovative examples of AI-powered solutions were highlighted during Africa Climate Week in Kenya in September. From climate-resilient supply chains and clean energy solutions for rural women to disaster risk reduction initiatives across the continent, cleantech and AI were celebrated as companions for the better. The Biosphere Reserves as Observatories for Climate Change Adaptation in Southern Africa (Be-Resilient) uses AI to predict flooding patterns in Mozambique. The Intergovernmental Authority on Development is harnessing AI to enhance impact-based forecasting by the Climate Prediction and Applications Center in East Africa’s agriculture sectors, which is key for food security, livelihoods, and economic development.
Yet AI doesn’t exist in a cleantech vacuum. Ethical cleantech requires companies and entities deploying AI to scrutinize and oversee it, keenly examining it for caliber, fairness, and security as they develop, deploy, and circulate products and services. Doing so will reduce or rectify risk where necessary.
Staking Claims for Ethical AI in CleanTech
Cleantech is crucial for mitigating the climate crisis that surrounds us. It can solve some of the world’s most complex problems, especially through automation and AI. It is also imperative for cleantech companies to build in ethical AI safeguards, though, so that, as Morrison Foerster writes in JD Supra, issues such as malfunctioning tools, data, or algorithms don’t emerge, and situations in which AI excludes certain persons, violates human rights, and compromises safety are eliminated.
An October, 2023 US White House Executive Order on the safe, secure, and trustworthy development and use of artificial intelligence notes that AI reflects the principles of the people who build it, the people who use it, and the data upon which it is built. Because humans vary in conformity to standards, ethical AI requires robust, reliable, repeatable, and standardized evaluations, especially, the White House says, “with respect to biotechnology, cybersecurity, critical infrastructure, and other national security dangers — while navigating AI’s opacity and complexity.”
For example, researchers performing tests have been able to successfully manipulate ChatGPT to generate false narratives. NewsGuard researchers were able to consistently bypass ChatGPT’s safeguards meant to prevent users from generating potentially harmful content. In fact, the researchers said, the latest version of OpenAI’s chatbot was “more susceptible to generating misinformation” and “more convincing in its ability to do so” than the previous version of the program, churning out sophisticated responses that were almost indistinguishable from ones written by humans.
The UN Climate Change Technology Executive Committee (TEC) will convene a high level event on AI for climate action at COP28, which starts today, in collaboration with the Climate Technology Centre and Network (CTCN) and the incoming COP Presidency. Part of this conversation will certainly surround concerns over ethical AI. That’s because major fossil fuel corporations pumped millions of dollars into digital advertising this year in the lead-up to the COP28 talks, elements of a broader campaign that has inundated social media with mis- and disinformation in an attempt to undermine climate science and action.
A new report from the Climate Action Against Disinformation (CAAD) coalition concludes that mis- and disinformation content not only impacts debate and implementation of climate policy but also centers climate as a vector for wider conspiracy theories, scapegoating, and social division. Their investigation reveals that over 150 ad exchanges are enabling the monetization of climate mis- and disinformation on 15 key websites, and 25 ad tech companies stand out as critical vendors, including exchanges owned by Microsoft, Google, Amazon, and Yahoo. CAAD adds that all platforms fall short in providing algorithmic reporting, and most lack reporting on misinformation trends.
The continued maturing of ethical AI in cleantech has the potential to extinguish existing challenges, including those of large scale mis- and disinformation. Instead of posing threats to the already fraught landscape of misleading claims about climate change, cleantech can mandate safeguards as part of practice and self-regulate egalitarian measures, even when governmental policies fall short of imposing ethical AI use mandates.
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