“For many years now, I’ve been working with citizen stakeholders in the southeastern corner of Massachusetts,” says Boutt, “and in 2021, the Pine Barrens Alliance, an environmental group interested in preserving the area’s unique environmental character, approached me with an idea for a project to help assess how communities along the coast could best prepare for climate change.”

Boutt and his colleagues, including recent UMass graduate and research assistant Alexander Kirshen, undergraduates Rachel King and Carly Lombardo, graduate student Daniel Corkran and postdoctoral researcher Brendan Moran, jumped at the opportunity to apply their academic research to an urgent, real-world problem close to home.

Plymouth sits on top of a freshwater aquifer — the town’s sole source of water. Because Plymouth extends to the ocean’s edge, it is extremely susceptible to rising sea levels. For their study, Boutt, Kirshen and colleagues peeked underground to see what was happening.

Groundwater, flowing beneath the surface of the land, and the ocean’s water, which, likewise, flows subterraneanly, push against each other and reach an equilibrium state. A well sunk on the freshwater side will flow with sweet water, but one that drills down into the brackish meeting point between fresh and salt will come up briny. As the oceans rise, that sub-surface saltwater pushes farther inland, and wells that have delivered pure water for generations can suddenly turn salty.

While the theory might seem intuitive enough, actually mapping, to say nothing of predicting, the flows and interactions of both fresh and salt water is an enormously complex task.

To start, the team built a salinity database that gathered all the available data from groundwater wells and surface water, such as ponds and streams, in the Plymouth area and measured them for salinity. This gave them a baseline understanding of the current locations and likely sources of elevated water salinity.

Next, Boutt and Kirshen adopted an existing U.S. Geological Survey hydrogeological model, which only focused on the onshore half of the hydrogeology equation, by extending its reach five kilometers offshore. The model includes ponds, streams, terrestrial recharge — or the rate and amount of precipitation that seeps down into the aquifer — as well the various wells that draw from the aquifer and the wastewater that is returned to the aquifer via re-infiltration or septic systems.

Finally, they conducted a series of model runs that took into consideration various scenarios in terms of future precipitation, sea-level rise, groundwater usage and changes in water returned to the aquifer.

“We found that, under the high sea-level rise scenario, areas of the aquifer will increase in salinity by up to 17,000 milligrams per liter by 2100,” says Kirshen, “and the mixing zone between the ocean and freshwater will migrate inland by up to 200 meters.” While a few ponds might see significant rise in water elevation, by up to 1.8 meters, most ponds would not see their salinity increase from this source of salinization.

The team also learned that water returned to the aquifer by septic systems plays a major role in helping to limit saltwater intrusion. “About 66% of the water that gets pumped out of the aquifer ends up returning to it,” says Kirshen.

Perhaps the biggest surprise is that the highest levels of salinity today aren’t near the coast, but inland, and especially around the roads. “This surprised me,” says Boutt, “and it looks like road salt is one of the main sources of elevated salinity today.”

“In partnering with UMass Amherst, we were always thinking beyond the municipal boundaries of Plymouth,” says SEMPBA Vice President Frank Mand. “We share an aquifer and a geological foundation with over 30 communities in our ecoregion. So, though the news for Plymouth is good, more importantly we now have a scientific foundation — and new methods for evaluating susceptibility to saltwater intrusion — that are transferrable to those other communities and will help inform Plymouth’s and other communities’ planning for years to come.”

“We were not looking to science to help us recover from our mistakes,” Mand adds. “We were seeking to avoid problems in the future. That, in and of itself, was a worthy goal.”

To prepare for the future, Boutt and Kirshen recommend further, finer-grained analyses of the region’s hydrogeography, the creation of an early warning system to monitor the sites most vulnerable to saltwater intrusion, developing new wells in areas that are at the least risk of salt contamination and reconsidering practices, such as salting the roads in the winter, which are currently responsible for the majority of saltwater contamination in the area.

Professor of International Security at Lancaster University Joe Burton argues that AI and algorithms are not just tools deployed by national security agencies to prevent malicious activity online, but can be contributors to polarization, radicalism and political violence — posing a threat to national security.

Further to this, he says, securitization processes (presenting technology as an existential threat) have been instrumental in how AI has been designed, used and to the harmful outcomes it has generated.

Professor Burton’s article ‘Algorithmic extremism? The securitization of Artificial Intelligence (AI) and its impact on radicalism, polarization and political violence’ is published in Elsevier’s high impact Technology in Society Journal.

“AI is often framed as a tool to be used to counter violent extremism,” says Professor Burton. “Here is the other side of the debate.”

The paper looks at how AI has been securitized throughout its history, and in media and popular culture depictions, and by exploring modern examples of AI having polarizing, radicalizing effects that have contributed to political violence.

The article cites the classic film series, The Terminator, which depicted a holocaust committed by a ‘sophisticated and malignant’ artificial intelligence, as doing more than anything to frame popular awareness of Artificial Intelligence and the fear that machine consciousness could lead to devastating consequences for humanity — in this case a nuclear war and a deliberate attempt to exterminate a species.

“This lack of trust in machines, the fears associated with them, and their association with biological, nuclear and genetic threats to humankind has contributed to a desire on the part of governments and national security agencies to influence the development of the technology, to mitigate risk and (in some cases) to harness its positive potentiality,” writes Professor Burton.

The role of sophisticated drones, such as those being used in the war in Ukraine, are, says Professor Burton, now capable of full autonomy including functions such as target identification and recognition.

And, while there has been a broad and influential campaign debate, including at the UN, to ban ‘killer robots’ and to keep the human in the loop when it comes to life-or-death decision-making, the acceleration and integration into armed drones has, he says, continued apace.

In cyber security — the security of computers and computer networks — AI is being used in a major way with the most prevalent area being (dis)information and online psychological warfare.

Putin’s government’s actions against US electoral processes in 2016 and the ensuing Cambridge Analytica scandal showed the potential for AI to be combined with big data (including social media) to create political effects centred around polarization, the encouragement of radical beliefs and the manipulation of identity groups. It demonstrated the power and the potential of AI to divide societies.

And during the pandemic, AI was seen as a positive in tracking and tracing the virus but it also led to concerns over privacy and human rights.

The article examines AI technology itself, arguing that problems exist in the design of AI, the data that it relies on, how it is used, and in its outcomes and impacts.

The paper concludes with a strong message to researchers working in cyber security and International Relations.

“AI is certainly capable of transforming societies in positive ways but also presents risks which need to be better understood and managed,” writes Professor Burton, an expert in cyber conflict and emerging technologies and who is part of the University’s Security and Protection Science initiative.

“Understanding the divisive effects of the technology at all stages of its development and use is clearly vital.

“Scholars working in cyber security and International Relations have an opportunity to build these factors into the emerging AI research agenda and avoid treating AI as a politically neutral technology.

“In other words, the security of AI systems, and how they are used in international, geopolitical struggles, should not override concerns about their social effects.”

As one of only a handful of universities whose education, research and training is recognised by the UK’s National Cyber Security Centre (NCSC), part of GCHQ, Lancaster is investing heavily in the next generation of cyber security leaders. As well as boosting the skills and talent pipeline in the region by building on its NCSC certified Masters degree with a new undergraduate degree in cyber security, it launched a trailblazing Cyber Executive Masters in Business Education.

The study, “Friend or Foe? Teaming Between Artificial Intelligence and Workers with Variation in Experience,” looks at the influence of two major types of human work experience (narrow experience based on the specific task volume and broad experience based on seniority) on the human-AI team dynamics.

“We developed an AI solution for medical chart coding in a publicly traded company and conducted a field study among the knowledge workers,” says Weiguang Wang of the University of Rochester and leading author of the study. “We were surprised by what we found in the study. The different dimensions of work experience have distinct interactions with AI and play unique roles in human-AI teaming.”

“While one might think that less experienced workers should benefit more from the help of AI, we find the opposite — AI benefits workers with greater task-based experience. At the same time, senior workers, despite their greater experience, gain less from AI than their junior colleagues,” says Guodong (Gordon) Gao of Johns Hopkins Carey Business School, and study co-author.

Further investigation reveals that the relatively lower productivity lift from AI is not a result of seniority per se but rather their higher sensitivity to the imperfection of AI, which lowers their trust in AI.

“This finding presents a dilemma: Employees with greater experience are in a better position to leverage AI for productivity, but the senior employees who assume greater responsibilities and care about the organization tend to shy away from AI because they see the risks of relying on AI’s assistance. As a result, they are not effectively leveraging AI,” says Ritu Agarwal of Johns Hopkins Carey Business School, a co-author of the study.

The researchers urge employers to carefully consider different worker experience types and levels when introducing AI into the work. New workers with less task experience are disadvantaged in leveraging AI. Meanwhile, senior workers with more organizational experience may be concerned about the potential risks imposed by AI. Addressing these unique challenges are key to productive human-AI teaming.

“Our results show that even in 2050 going off-grid won’t be the most economic choice, but it could make sense to invest in these kinds of self-sufficient buildings if you are willing to pay more for self-sufficiency,” says lead author Max Kleinebrahm, an energy economics researcher at the Karlsruhe Institute of Technology in Germany.

Grid energy costs are rising while renewable energy technology is becoming more affordable. In pursuit of self-sufficiency, more and more households are showing interest in producing their own renewable energy supplies. Kleinebrahm’s team wanted to know how feasible it would be for individual residential buildings in different parts of Europe to become fully self-sufficient, and whether doing so would come with any financial benefits. Though the potential of converting Europe to 100% renewable energy has been considered at the continental, national, and regional scale, this study is the first analysis at the level of individual buildings.

To identify regions and building types that are more amenable to self-sufficiency, the researchers compiled a database of homes across Europe and identified 4,000 homes that were representative of different regions in terms of architecture, household electricity demand, climate conditions, and the local economic framework. Then, the researchers designed optimal energy systems for each representative home that would fully cover electrical and thermal energy needs while minimizing costs. These systems included measures such as rooftop solar panels, small wind turbines, different types of storage systems, heat pump installation, and retrofitting and insulation measures.

Next, the researchers scaled their results up to estimate the technical and economic feasibility of energy self-sufficiency for Europe’s 41 million freestanding single-family homes. Overall, they estimated that 53% of homes could have technically achieved energy self-sufficiency in 2020, and that this proportion could increase to 75% by 2050 with expected improvements in renewable energy and storage technologies. However, becoming fully self-sufficient was more expensive than remaining fully dependent on the grid, both in 2020 and 2050.

Homes in sunny European countries such as Cyprus, Malta, and Italy have more economic potential for self-sufficiency, while northern European countries such as Finland, Norway, and Sweden (where there is a large mismatch between high winter energy needs and solar radiation) have the lowest potential. Regions with larger rooftops, such as Denmark, Slovenia, the Netherlands, and France, also have greater potential for self-sufficiency. The researchers also noted that there is greater potential for self-sufficient buildings in countries with high on-grid electricity costs, such as Germany, since there is less financial incentive to remain on-grid.

Though becoming fully self-sufficient may not be economically advantageous, the researchers demonstrated that partial self-sufficiency — where a building remains connected to the electricity grid but also invests in a photovoltaic system, heat pump, and insulation — could lower household energy costs. The optimal degree of self-sufficiency varied for different buildings and regions, but for one representative building in Germany, the researchers estimated that it would have been cost-optimal to be 73% self-sufficient in 2020 and 78% self-sufficient in 2050.

The researchers note that high carrier costs make leaving the grid more appealing and say that policymakers and utility companies should encourage even fully self-sufficient households to remain connected to the grid. “At a macroeconomic scale it would be less efficient to have a large number of households abandoning the grid rather than supporting it,” says Kleinebrahm.

Since the costs of supporting the grid are shared amongst users, there is also the potential for grid costs to climb further as households choose to leave the grid. “From the social perspective, you have to consider the possibility that very rich households could go off grid, in which case the rest of the grid operation would have to be paid for by economically weaker households,” says Kleinebrahm.

This study is unable to answer questions about how the expanding number of self-sufficient homes would impact electricity demand and electricity markets, but the researchers plan to address those topics in future.