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Hello and welcome to Eye on AI. Copyright issues continue to dominate AI news this week. First, U.K. newspaper the Telegraph surfaced a submission OpenAI made to the British House of Lords, which is considering whether to update the country’s copyright laws to address issues raised by generative AI. In the submission, OpenAI claimed creating “leading AI models” would be “impossible” without using copyrighted material and that relying instead on text in the public domain would result in AI that fails to “meet the needs of today’s citizens.” Related Video The U.K. already has a copyright exemption for “text and data mining” that applies to noncommercial research projects (it happens to have also led to concerns about nonprofits being set up to engage in “data laundering” for businesses). But now OpenAI is arguing that the country should create a similar exemption for all AI model training. Without a right to use copyrighted material for training, OpenAI claims, ChatGPT would cease to exist. As many have pointed out, OpenAI’s submission is, at best, disingenuous. It fails to discuss the option of licensing copyrighted material for training—in fact, fails to note that OpenAI itself is currently pursuing such licenses for at least some training data, while simultaneously arguing it is impossible. Other companies have also managed to create good generative AI models without taking copyrighted material without consent (more on that in a minute). If companies want to argue that finding rights holders and obtaining licenses is too onerous, there are even some other creative options. It might be possible for the government to establish a fund, paid for by a tax on the sale of generative AI models, to which rights holders could apply for compensation. This is exactly the approach the U.S. Congress once took for recording artists with the 1992 Audio Home Recording Act. Of course, not all of OpenAI’s negotiations over licenses have gone swimmingly. On Monday, the company also posted a blog responding to the New York Times’ copyright infringement lawsuit against it. In the blog, OpenAI said the newspaper’s lawsuit was “without merit.” It also says that it had thought negotiations with the newspaper were proceeding well, with discussions continuing up until Dec. 19, and that it had been “surprised and disappointed” when the newspaper unexpectedly filed suit against it on Dec. 27. But OpenAI hinted that there was likely a big chasm between what the New York Times was demanding and what OpenAI was willing to pay. It said it had tried to explain to the newspaper’s representatives that “like any single source, their content didn’t meaningfully contribute to the training of our existing models and also wouldn’t be sufficiently impactful for future training.” In other words, OpenAI was trying to get away with offering the Times peanuts. The Times no doubt felt it deserved sirloin steak (or a crab cake, at least). OpenAI’s framing of its position helps explain why negotiations with copyright holders are going to be so contentious. If the tech companies are forced to pay for data, they only want to pay for the marginal information value that data provides the model. These large language models ingest so much text that in most cases, as OpenAI argues, the value of any one source—even the New York Times with its reputation for journalistic excellence and vast archive of millions of articles—is minimal. But many rights holders are not primarily concerned with the information value of their data. They are mostly worried about the threat that trained model will pose to their future revenue. If people come to rely on chatbots to summarize the news and do research for them, no one will actually visit the New York Times website. So the revenue loss could be large. Rights holders feel they should be compensated to some degree for that potential loss. Bridging this gap will likely require an adjustment of expectations on the part of both sides—much as happened with music streaming. In its blog post, OpenAI also says that the New York Times, in its lawsuit and accompanying exhibits, has not been candid about how easy it is to produce copyright-infringing material using OpenAI’s models. The lawsuit included hundreds of examples in which the paper said it was able to get ChatGPT and other OpenAI models to spit out verbatim copies of stories when prompted with a snippet from the original but no explicit instruction to produce a Times’ story. OpenAI tried to characterize this “regurgitation” as a rare bug (more on that in a moment too) and that the New York Times either was not disclosing its prompts accurately or had cherry-picked its examples from thousands of attempts. OpenAI said regurgitation was more likely to occur when a single piece of text has been ingested multiple times during training, as was more likely to happen with Times’ stories because they are syndicated and reprinted in many other publications. But here again, what OpenAI says is misleading. It is becoming increasingly apparent that regurgitation is not some highly unusual bug but a relatively common feature of most generative AI models. Last week, Gary Marcus, emeritus New York University cognitive scientist and prolific AI commentator, and Reid Southen, a commercial film concept artist, collaborated on research published in IEEE Spectrum that showed how easy it is to get both Midjourney’s latest text-to-image generator and OpenAI’s DALL-E 3 to regurgitate—or, as Marcus and Southen said, “plagiarize”—copyrighted content. They showed that it was trivial to get the models to produce Marvel, Warner Brothers, and Disney characters, including images that were nearly identical to film stills the studios released. They showed this could be done even without naming the movie or the characters. For Midjourney, they demonstrated that simply using the prompt “screencap” was enough to produce content nearly identical to copyrighted film stills. (Midjourney did not respond to a request to comment for this story.) Researchers have previously shown it is possible to get LLMs to leak training data in their outputs, including personally identifiable information. It has also been shown that some images are so iconic that it can be difficult for image-generating models not to copy them in their outputs. A classic example by now is the prompt “Afghan girl” which in early versions of Midjourney always returned an image strikingly similar to Steve McCurry’s famous National Geographic cover photo. Midjourney has since disallowed that prompt and OpenAI seems to have tweaked DALL-E to force the model to return a different sort of image. But the point is regurgitation isn’t some rare quirk. It’s an inherent problem with how all LLMs work, one that has to be addressed by post-generation filtering, specific fine-tuning, or prohibiting certain prompts. Marcus has been quick to claim these copyright issues mean that OpenAI’s business model is broken and that it, and the whole rest of the generative AI boom, is about to collapse as a result. I don’t think that will happen—although I do think business models may have to change. This week, I spoke to the CEO of one company that shows that it is possible to get on the right side of these issues and still make a buck: Getty Images. It has partnered with Nvidia to create a generative AI still image product, which it made available through its iStock service this week, as well as with Runway on a forthcoming video generation product. Getty CEO Craig Peters tells me the company is committed to “commercially safe” generative AI. He says this means its AI offerings have been trained only using Getty’s own library of licensed images, they won’t output images of celebrities and other people that might cause commercial rights issues, and they won’t output any trademarked logos or characters either. Even though Getty already had a right to use these images, Peters says the company wants to ensure creators receive additional compensation for their contribution to generative AI. Getty has done this by giving anyone whose images are part of the training base a share of the revenue the company brings in from its generative AI product. Right now, this is allotted according to the proportion of the overall training set that the creator represents and also a metric for how often their imagery is currently being purchased from Getty’s stock catalogue. Peters says this second figure serves as a proxy for content quality. He says that in the future he would be in favor of a system that would reward creators for their contribution to any particular AI output, but that the technology to do so doesn’t currently exist. Getty’s experience proves that copyright issues around generative AI can be overcome. Sure, it helps if business models align. Neither Getty’s nor Nvidia’s existing business was cannibalized by the new product. OpenAI and the New York Times are in a trickier situation. Any product the Times helps OpenAI build would likely cannibalize its existing advertising and subscription model. But a deal would only be “impossible” if one uses OpenAI’s favored definition of the word.

Alphabet, Meta Platforms and OpenAI are reportedly in talks with Hollywood studios to license content for their artificial intelligence video generation software. The companies are developing technology that can create realistic scenes based on text prompts and have offered financial incentives to partner with studios, Bloomberg reported Thursday (May 23). The discussions come as studios look for ways to use AI to lower costs while protecting their intellectual property, according to the report. Studios are cautious about providing their films and TV shows to tech companies without control over how the content is used, the report said. The recent case of Scarlett Johansson demanding OpenAI to stop using a voice resembling hers in its chatbot highlights the concerns of actors and creators about the use of AI technology. The potential financial gains from licensing content to AI companies are substantial, per the report. News Corp. this week agreed to allow OpenAI to use content from its publications in a deal worth over $250 million over five years. Warner Bros. Discovery has expressed interest in licensing some of its programs, while Walt Disney Co. and Netflix have shown interest in other types of collaborations but are not willing to license their content.

Local journalism is a cornerstone of democracy and a vital source of information for communities across the country, with newsrooms covering local politics, high school sports, local business, cultural events and other matters that help a community remain vibrant and connected. However, the industry is facing an existential crisis because of the unyielding power of Big Tech platforms such as Google and Facebook. With less than four weeks left in this Congress, now is the time for the Senate to pass the Journalism Competition and Preservation Act. The act was favorably reported out of committee in September with strong bipartisan support and now must head to the floor for a vote. It will hold tech giants accountable and provide a necessary lifeline for local papers, requiring Big Tech to compensate small and local outlets for the use of their content. Big Tech benefits tremendously from journalism content, yet they refuse to pay local publishers fairly for the journalistic content that fuels their platforms. As a result, local papers are being replaced by tech platforms using black-box algorithms designed to keep users inside their walled gardens — all while charging exorbitant ad fees — up to 70 percent of every advertising dollar. The tech giants have built their empires by profiting off the hard work of journalists without fairly compensating them. As local publications struggle to stay afloat, Big Tech has only doubled down on their anticompetitive practices, further consolidating their control over the flow of information. This is fundamentally unfair, and the Journalism Competition and Preservation Act will bring about much-needed change. The act will benefit small and local publishers exclusively and impose severe penalties if the tech platforms do not negotiate with them in good faith. The bill has a limited scope of six years to address a broken marketplace, while the broader competitive landscape is fixed through other legislation and the courts. It also incentivizes publishers to hire more journalists and protects constitutional freedoms of speech and the press. The bill’s scope is limited to compensation and does not allow for negotiations around up-down ranking or display — it serves only to ensure fair compensation for local news outlets. The Journalism Competition and Preservation Act has strict transparency requirements on the terms of each agreement reached between tech platforms and journalism providers and establishes clarity in how news outlets spend the funds they receive. News publishers around the world are being compensated by Big Tech. Australia passed a similar policy, the News Media Bargaining Code, for media organizations to bargain for payment, which has produced significant revenue — billions of dollars, if translated to the U.S. market — for hundreds of publications of all sizes. One Sydney journalism professor noted that she hadn’t seen her industry so financially robust in decades. There are so many open positions for reporters, they cannot all be filled, a signal of the improved economic health of the industry. The swift and clear successes of the Australian code — and efforts in other countries such as Canada, the U.K., European Union and more — should serve to encourage the passage of the act in the United States. Thousands of hometown papers from across the political spectrum, as well as both Democrats and Republicans in Congress, support the Journalism Competition and Preservation Act. Moreover, during highly polarized times, polling data found that 70 percent of Americans support this legislation as well. The act has such broad support because it is, essentially, about basic fairness. Local papers cannot afford to endure several more years of Big Tech’s use and abuse. The time we have to take action is dwindling. If Congress does not act soon, we risk allowing social media to become America’s de facto local newspaper. The Senate must advance the Journalism Competition and Preservation Act to the Senate floor for a vote before the end of the year to rein in Big Tech and restore fairness to local journalism — one of the most important checks and balances we have against corporate power and government corruption — before it’s too late.

For roughly 80 years, the United States has managed the threat of nuclear terrorism through nonproliferation treaties, agency programs, intelligence activities, international monitoring support and more, withstanding the Cold War, the fall of the Soviet Union, and 9/11. A National Academies committee led by Northeastern University’s Stephen Flynn wants to ensure the U.S. remains prepared. “The issue of nuclear terrorism remains very much a real one, there are enormous stakes involved and the risks are high, but the issue has been falling off the radar screen of the American public over the last 15 years, and the skill set of people involved in managing it is aging out,” says Flynn, professor of political science and founding director of the Global Resilience Institute at Northeastern. “We really need to keep our eye on the ball. It was quite timely for Congress to call for an assessment of this risk and provide recommendations for staying on top of this issue.” In the 2021 National Defense Authorization Act, Congress mandated the U.S. Department of Defense and the U.S. Department of Energy’s National Nuclear Security Agency to work with the National Academy of Sciences, Engineering and Medicine to assess the current state of nuclear terrorism and nuclear weapons and materials and advise the government on how to handle such issues. Flynn, an expert on national and homeland security, was appointed chair of the committee in 2022. The committee . The report finds that a lot has changed since the issue of nuclear terrorism was forefront in Americans’ minds following 9/11 and the buildup to the Iraq War. “We had a war on terror after 9/11, but that didn’t succeed in eliminating the terrorism threat,” Flynn says. “Terrorism continues to morph.” The outbreak of the Israel-Hamas War, which occurred as the committee finalized its report, demonstrates this morphing of terrorism. The involvement of Hezbollah as a proxy of Iran, and the involvement of Hamas — both groups are by the U.S. State Department — highlight a world where non-states and nuclear-seeking states collaborate in warfare, Flynn says. “The designation between non-state vs. state actors is blurry,” Flynn says. “The assessment reveals we have to be focused on where those two things may overlap.” Also “blurring” is the line between domestic terrorism and international terrorism, Flynn says. “Particularly when you look on the far right, international terror groups are recruiting Americans into these organizations, and Americans are reaching out to extremist organizations that have terrorism elements,” Flynn says.

The global proliferation of artificial intelligence (AI) technology has shortened the distance between cyber warfare and military conflict. Modern warfighters have developed and embraced autonomous weapons programmes to fight wars across domains. As a result, AI technologies have raised the chance that military personnel may use autonomous systems to launch cyber operations during military operations (Guembe ). AI programmes may also enable military officials to deploy cyber means more effectively to destroy their adversaries and consequently, deepen human reliance on the use of cyberweapons as a means of planning and winning battles. The weaponisation of AI technologies, ranging from image recognition to text analysis to game playing, leaves tremendous implications for the use of violence. Yet we do not know how exactly AI, cyberwarfare, and traditional military conflict are connected.

This question is critical because there is no scholarly effort to link two important phenomena taking place – AI reshaping strategic discourse and “cross-domain operations.” In the literature of international security, there is little to no work on how AI would affect war fought across cyber and military domains. As a result, we do not know how machines may affect the balance of power between major powers like Russia, the United States, and China that have increased investment into AI research and development (R&D) and intensified the AI arms race (Kostyuk and Gartzke ). In this paper, I take up the notion of “cross-domain warfare” to explore how AI affects the relationship between cyber and military operations that states carry out.

Food crises are a recurring issue that impacts a significant number of impoverished families in developing countries and they often lack access to sufficient public assistance. This study focused on Latin America, a region that presented waves of food riots during and after such crises. Our primary concern was with the well-being of the rural poor, who face additional obstacles due to their geographical distance from centers of political power and comparatively limited support systems within their respective countries.

The empirical analyses conducted for Latin America largely supported our initial hypotheses. Furthermore, some of the results regarding the explanation of statistical models based on the data for the Latin American region were confirmed in models for countries worldwide. For instance, the association of food riots with (1) employment in agriculture; (2) political polarization; and (3) inequality were consistent. On the other hand, another set of variables including (1) land grab area; (2) tenure security; (3) arable land; (4) urbanization; and (5) hybrid regimes demonstrated statistical significance exclusively for the Latin American region, with its unique characteristics. This, in itself, validates the focus of this research on Latin American countries.

Cryptocurrency is also used to raise funds for terrorist organizations and other nation state threat actors, although cases involving cryptocurrencies are less prevalent than those involving traditional financial assets.17 For instance, in 2020, the Department announced the government’s largest-ever seizure of cryptocurrency in the terrorism context. This action disrupted al-Qassam Brigades, alQaeda, and ISIS (Islamic State) fundraising campaigns, including a scheme in which ISIS attempted to exploit the COVID-19 pandemic by operating a fraudulent website purporting to sell N95 masks and other personal protective equipment.18 And in 2018, the Department charged twelve members of the GRU, a Russian Federation intelligence agency, with committing federal crimes intended to interfere with the 2016 U.S. presidential election. The indictment alleged that the defendants attempted to avoid detection by, among other things, funding the operation with cryptocurrency earned by mining bitcoin.19 Rogue states have also turned to cryptocurrency theft in an effort to raise funds. The United States and the United Nations have implicated the Democratic People’s Republic of Korea (DPRK), for example, in a number of cryptocurrency heists and other related criminal activity.20 In March 2022, Lazarus Group, a hacking group sponsored by the DPRK, stole over $600 million from a blockchain project linked to an online gaming platform.21 Regulatory actions taken in response to this theft are discussed in Part III below.

Effective anti-money laundering and combating the financing of terrorism (AML/CFT) policies and measures are key to the integrity and stability of the international financial system and member countries’ economies. Money laundering (ML) and related underlying crimes (the so-called “predicate offenses” or “predicate crimes”), as well as terrorist financing (TF) and the financing of the proliferation of weapons of mass destruction (WMD) or proliferation financing (PF) are crimes with economic effects—they can threaten the integrity and stability of a country’s financial sector and a country’s external stability more generally. They can result in destabilizing “hot money” resulting from inflows and outflows, as well as in banking crises, ineffective revenue collection, broader governance weaknesses, reputational risks for international financial centers, and loss of correspondent banking relationships (CBRs). In an increasingly interconnected world, the harm done by these crimes is global, affecting the integrity and stability of the international financial system. AML/CFT policies and measures are designed to prevent and combat these crimes and are essential to protect the integrity and stability of financial markets and the global financial system.

Since the advent of the internet, online shopping has gone from a rarity to a necessity.3 The Department of Commerce estimates that in 2020, e-commerce sales amounted to 791.7 billion which was a 32.4 percent increase from 2019.4 In the fourth quarter of 2020 alone, e-commerce sales accounted for 15.7 percent of all total retail sales for the quarter, amounting to approximately $245.3 billion.5 Online shopping is drastically more efficient than traditional in-person shopping.6 Online shoppers tend to find better deals, a larger variety of products, and easier methods of product comparison than they would find in traditional stores.7 As a result, brick-and-mortar stores are closing at record rates.8 More than 11,000 stores closed in 2020, with the trend likely to continue well into 2021 as the COVID-19 pandemic continues to ravage the traditional storefront model. 9 Consumers rely on online shopping when purchasing their everyday essentials-buying brands they know and trust. But is the product they buy online actually the same as the one in stores? Although consumers think they are getting the same product from the same brand they know and trust online, the mysterious process of order fulfillment often means the consumer receives a counterfeit product in lieu of the authentic product.10 While receiving a counterfeit iPhone charger may seem inconsequential to consumers, receiving a counterfeit N95 mask would have dire consequences in the COVID-19 pandemic. 1 Online marketplaces such as Alibaba, Amazon, and eBay are actively expanding into markets traditionally reserved for brick-and-mortar stores.12 When consumers shop at these online marketplaces, they often see products and brands they trust at a fraction of the cost.13 Once consumers enthusiastically purchase the product, the possibility that the item may be a counterfeit rarely crosses their mind. Some consumers will realize that they received a counterfeit item as soon as they open the box; some will realize when they go to use the product and it fails to function properly; and some will not realize it until there are devastating consequences, such as injury, sickness, or death. The pervasiveness of counterfeits on these online storefronts is the result of insufficient policing of trademark infringements by the online marketplaces. 1 4 In order to protect trademarks and to ensure the safety of consumers, a uniform system for reporting and enforcing infringements for online merchants must be established. In addition, creating stronger legislation to hold online merchants contributorily liable for counterfeits would incentivize platforms to diligently police counterfeit products on their websites. Tiffany v. eBay is the landmark case addressing trademark infringement in the realm of counterfeit products that are sold on online marketplaces.1 5 Tiffany is a world-renown luxury jewelry retailer that exclusively sells its branded jewelry through its own retail stores, website, catalogues, and Corporate Sales Department. 16 eBay is an online marketplace that facilitates registered users to buy and sell products amongst one another." Although eBay "provides the venue for sale [of goods] and support for transaction[s], it does not itself sell the items listed on the site," nor is it ever in physical possession of the items.18 eBay attempted to take steps to monitor counterfeit listings, however, the problem persisted, 19 and Tiffany sued eBay for contributory trademark infringement for facilitating the counterfeit product listings' use of their trademarks.2 When Tiffany lost its case in the district court it appealed to the Second Circuit.2 1 The Second Circuit agreed with the district court's holding that although eBay generally knew that there were counterfeit items on their website that infringed upon Tiffany's trademarks, general knowledge is insufficient to hold a service provider liable for contributory infringement.2 2 In addition, the court stated that Tiffany did not demonstrate eBay's continued sale of infringing products after Tiffany notified them of the specific infringements. 23 This case is the reason that service providers are under no affirmative obligation to police counterfeits, and instead the burden rests on the trademark owner.24 The sheer quantity of products online makes it untenable for trademark owners to accurately police every listing, and it can be difficult for a trademark owner to determine whether a listed product is authentic, sold under the first sale doctrine, or is a counterfeit simply by looking at a listing.25 Often listings will utilize pictures of authentic popular brands in their product description while the actual product for sale is a counterfeit-thereby violating trademark rights and risking consumer safety.26 For example, an Amazon listing for a "4 in 1 Baby Car Seat and Stroller" included images of the popular car seat brand Doona, but the list price was approximately $200 cheaper than the real Doona. 27 Unsurprisingly, the listed car seat was actually a knock-off of the Doona car seat. 28 The counterfeit seat failed to meet basic safety standards, endangering the countless children still sitting in them.29 Service providers have more authority and better resources to actively screen products listed on their websites, but they can be hesitant to do so.30 Consumers are subjected to deceptive business practices and potentially dangerous counterfeits, while service providers facilitate sales with impunity and without oversight. 3 1 The court's holding in Tiffany enables service providers to take a hands-off approach to the trademark infringements occurring on their platforms. 3 2 The lack of liability on the part of service providers harms both brand owners and consumers and should be remedied through consistent policing of infringements by all parties involved: service providers, brand owners, governments, and consumers. 33

The advent of agricultural IoT has fueled the integration of IoT technology across various aspects of agricultural irrigation management. However, certain challenges persist in current intelligent agricultural irrigation management, including the following: (1)Data security issues: Data security and privacy are critical concerns in IoT, and the information communication process in agricultural irrigation management is vulnerable to various security attacks. For example, ZigBee is susceptible to data manipulation and packet decoding, while WiFi is susceptible to interference and passive attacks. Thus, future efforts must focus on enhancing security measures to prevent data breaches, losses, or hackers and provide data security and privacy. (2)Data fusion issues: As the agricultural IoT technology advances, the volume of agricultural irrigation data is growing exponentially, leading to increasingly complex and diverse irrigation status information. To achieve precise irrigation, significant amounts of state information must be collected, analyzed, and stored. In future work, it is crucial to address the challenge of integrating multiple types of data from various sources, as well as establishing a comprehensive network to enhance the efficiency of data transmission. (3)Cost issues of agricultural irrigation management systems: Irrigation is not limited to greenhouses or small-scale farmland. In large-scale farmland and complex environments where irrigation network communication is required, equipment usage and maintenance costs must be taken into account. Additionally, more environmental parameters need to be measured at irrigation sites, necessitating the deployment of a large number of IoT devices. However, high-quality IoT equipment can be expensive, which puts an unnecessary financial burden on farmers. Thus, it is imperative to introduce high-precision, low-cost equipment, and choose affordable communication technology and networking methods to minimize IoT costs. (4)Multimedia data transmission issue. Due to the low bandwidth of long-range and low-power communication technologies like LoRa and NB-IoT, transmitting image data can result in low efficiency and quality. Images have large data sizes, leading to significant delays and slow transmission speeds. Moreover, data packets of images may get lost or corrupted, causing a partial loss of image information. Traditional image compression algorithms can lead to image distortion, blurriness, or loss of details. Therefore, future research needs to focus on image data compression techniques and transmission optimization strategies specifically tailored for long-distance communication using LoRa and NB-IoT, aiming to improve the efficiency and quality of image transmission. (5) and energy issues: Power and energy management are critical aspects of IoT-based deployments in agricultural irrigation applications, where power is a necessary tool and all devices used for communication, monitoring, and storage purposes require energy. Frequent battery replacement is required for certain communication equipment, which indirectly increases costs and is not conducive to energy consumption control in agricultural irrigation systems. Therefore, it is essential to develop advanced methods for strengthening the management of the sensing and communication aspects of IoT to optimize performance and control energy consumption. It is also important to focus on the use of to mitigate the energy demand of the deployed system. (6)System equipment failure: The agricultural irrigation IoT system should be resilient enough to prevent the failure of any single piece of equipment from affecting the overall operation of the system. The deployed irrigation system may face various failures, with hardware equipment failure being the most common. To increase the reusability and customization of system components and services, modular hardware and software components should be considered. The system design should be robust enough to enable the quick detection of system failures and facilitate reconfiguration and self-healing. The emergence of agricultural IoT is an inevitable development in intelligent and informationized agricultural irrigation management. Although it holds immense potential, there are myriad challenges on the way to its full development. In future research, increased emphasis should be placed on wireless communication technology. The existing intelligent irrigation system should be improved to meet the needs of agricultural irrigation, allowing for the fine adjustment of the irrigation system, on-demand irrigation, and automatic control. Additionally, sensor technology and electronic communication technology should be combined with IoT to ensure comprehensive benefits in agricultural production.

Water is a vital component in agricultural production, playing a significant role in plant growth. To achieve better agricultural production levels, it is crucial to provide essential and sufficient water at the right time [1]. However, in some regions, traditional irrigation methods are used, with farmers relying on their experience to determine irrigation time and water consumption. This approach fails to meet crop irrigation standards, leading to significant water and manpower waste [2]. One of the key technologies to enable precision is water management in irrigation systems. Unsuitable irrigation can lead to a decrease in crop yields, emphasizing the need for efficient irrigation in agricultural irrigation management. To provide accurate information about irrigation needs in real time, modern communication technologies such as the IoT and big data can be leveraged [3]. The Internet of Agricultural Things is a network that links agricultural information-sensing devices to the Internet, connecting agricultural production factors and the environment. Through the exchange and communication of information, it intelligently identifies, monitors, tracks, and manages agricultural processes and objects. Combining the IoT with traditional agricultural production methods shifts agriculture from a human-centered production model that relies on isolated machinery to a software-centric production model. This approach requires a large number of automated, intelligent, and remote production equipment. The improvement of agricultural IoT technology in the new era can reduce the cost of agricultural production and increase agricultural profitability. By utilizing IoT technology, various agricultural parameters such as soil moisture, weather conditions, and crop status can be monitored. These parameters can help farmers make timely decisions. For example, based on parameters such as soil moisture and rainfall, the water requirements of crops can be determined, and irrigation plans can be adjusted accordingly. Similarly, soil pH can be adjusted based on soil conditions to provide a suitable soil environment for different crops [4]. Fertilizer types and quantities can be determined based on measurements of soil nutrient levels at specific locations. This can improve fertilizer efficiency and reduce environmental side effects [5]. Accurate pesticide application plans can be formulated based on crop growth status, pest and disease risks, and other factors. This can reduce the improper use of pesticides and mitigate environmental pollution risks [6,7]. The above examples illustrate that the use of IoT not only enables timely action based on accurate information but also facilitates the management and on-demand utilization of agricultural resources such as water, fertilizers, and pesticides. This achieves cost savings and improves production outcomes. With the use of IoT technology, farmers can predict crop yields and market demand [8]. Planned and targeted agricultural production can be carried out based on market demand, thereby reducing economic losses and improving cost-effectiveness. In agriculture, the use of IoT devices such as automated machinery can automate labor-intensive tasks, reducing the need for manual labor and lowering labor costs. The reduction in manual labor and improvement in automation levels will enhance productivity in every aspect of the agricultural sector [9]. The general trend of the Internet of Things in agriculture is to use artificial intelligence technology and IoT wireless communication technology to create a smart agricultural irrigation technology system [8] Wireless communication technology can play a very important role in agricultural irrigation management, which is mainly used in central control systems, field-monitoring systems, control terminals, and pressure-sensing systems. The combination of wireless communication technology and artificial intelligence (AI) can provide intelligent decision support for irrigation systems. Data such as soil moisture and weather conditions collected by sensors are transmitted to the central control system through wireless communication technology. The system utilizes AI algorithms, machine learning, and data models [10,11,12] based on historical and real-time monitoring data to provide farmers with irrigation decision recommendations and optimization plans. This enables farmers to make scientifically sound irrigation decisions. The integration of wireless communication technology and AI allows for the remote monitoring and management [13] of irrigation systems, along with system warnings. The environmental data and real-time status of irrigation equipment are transmitted to user terminals through wireless communication technology, allowing users to remotely monitor the operational status of irrigation equipment through mobile phones, tablets, and other devices [14]. With AI algorithms, the system can automatically detect anomalies and faults in irrigation equipment and promptly notify farmers to take repair measures, thereby improving the efficiency of irrigation system operation. It can also provide early warnings for disasters, pests, and diseases, and initiate emergency measures, thereby reducing crop losses and economic losses [15]. Most importantly, compared to traditional manual irrigation, this approach helps achieve water-saving goals in agricultural irrigation systems [16]. IoT sensing devices enable the real-time monitoring of soil moisture, weather conditions, and other parameters. The data are sent to the central control system through wireless communication technology, where AI algorithms process and perform predictive analysis on the data. This assists farmers in making scientifically sound irrigation decisions and adjusting irrigation plans in a timely manner, enabling precise on-demand irrigation and reducing excessive and unnecessary irrigation. This greatly minimizes water wastage [17], which is of great significance in water-scarce areas. Climate change can lead to drought or insufficient water supply in regions with water scarcity [18], resulting in environmental issues such as soil salinization and groundwater depletion [19]. By employing IoT and AI technologies in irrigation systems, it is possible to provide crops with adequate water under limited water resources, enhancing drought resistance and ensuring the stability and sustainability of agricultural production. Additionally, it promotes water resource conservation, improves the sustainable utilization of water resources, and protects the ecological environment. This paper summarizes the existing research on various commonly used wireless communication technologies in the transmission layer of IoT networks. It also explores the application of these wireless communication technologies in agricultural irrigation management, analyzing their merits, limitations, and applicable scenarios. Furthermore, the challenges that arise when using IoT wireless communication technology in agricultural irrigation management are identified and discussed for future consideration.

IoT as an enabler of sustainability The integration of IoT technology into tech stacks plays a pivotal role in advancing sustainability efforts across various sectors. Here are some key areas where IoT is making a significant impact on sustainability: 1. Energy Efficiency | IoT-enabled devices can monitor and optimize energy consumption in real-time, leading to reduced wastage and lower carbon footprints. Smart meters, for instance, enable consumers to track and adjust their energy usage, fostering a culture of responsible energy consumption. 2. Waste Management | IoT-based sensors and tracking systems optimize waste collection routes, leading to efficient garbage disposal and reduced fuel consumption. Smart bins with fill-level sensors notify waste management authorities of when they need emptying, eliminating unnecessary trips and promoting recycling. 3. Agriculture and Water Management | By utilizing IoT sensors and data analytics, farmers can optimize irrigation, monitor soil moisture levels, and prevent water wastage. This precision agriculture helps conserve water resources and enhance crop yields, promoting sustainable farming practices. 4. Transportation and Logistics | IoT facilitates smart transportation systems that optimize traffic flow, reduce congestion, and minimize fuel consumption. Additionally, IoT-powered supply chain management enhances efficiency by enabling real-time tracking, monitoring, and predictive maintenance, reducing delays and waste. 5. Sustainable Buildings | IoT-enabled smart buildings leverage data analytics to optimize energy consumption, improve indoor air quality, and enhance occupant comfort. Automated systems control lighting, heating and cooling based on occupancy, reducing energy waste and operational costs.

Since Malthus wrote his famous Essay on Population, the world has witnessed great improvements in numerous measures of well-being – life expectancy, infan tmortality, incidence of famines and plagues, per capita food consumption as well as real per capita incomes. These improvements have come about during rapidpopulation growth in both industrial and developing countries. Food demand andsupply projections suggest that growth of supply will fully meet growth ofconsumption while grain prices continue to decline. While China may increasegrain imports early next century, Central and Eastern Europe is likely to emergeas a major grain exporter and thus help to meet the increase in China's imports.The past two centuries, and especially the last half century, have witnesseddramatic improvements in the well-being of the world's population, unpar-alleled in human history. This is especially true of the increases in percapita food consumption. Other measures of well-being, however, such aslife expectancy and freedom from famine, have also shown markedprogress. Yet, during recent years, claims have been made that the worldis (or soon will be) overpopulated. Some have claimed that the growth ofworld demand for food will soon outpace the growth of supply. The factthat similar claims, made over the past three decades, have all proved tobe false seems always to be forgotten.Reputable studies of prospective food supply and demand conclude that there will be continued improvement in per capita food consumption,especially in the developing countries (see Islam 1995). Yet the projectionsof doom and gloom continue to make headlines and receive mediaattention. The potential accuracy of such projections seems irrelevant sincenotice depends solely on the emphasis on possible disaster while moresober and well documented studies receive little attention in the world'spress.That pessimism makes news is well illustrated by the fact that Thomas Malthus is remembered for his comparison of the growth paths of foodproduction and population. Food production, he said, increases arithmet-ically while population, if unchecked, increases geometrically. Thus,population always has the potential to outrun food supply. At the timethis statement was made, his view was that population could only be heldin check by vice and misery – starvation, disease or war. But, this is theMalthus of the Ærst edition. 1 He soon revised his views, yet hardly anyonenoticed or remembers that he came to agree with those who, before theÆrst edition of his essay, believed that there would be continuing improve-ment in the well-being of people.2

Modern conflicts are almost never driven by a single cause. Food insecurity is often referred to as “the straw that breaks the camel’s back” or a “threat multiplier” in conflict events. It is true that food insecurity alone is often not enough to produce conflict; it must also be met with external motivators that cause people to resort to violence, and is strongly determined by the underlying social, political, and economic context. Those motivators can be captured in three interrelated concepts: desperation, grievance, and governance. Often, the strongest motivator for participation in conflict is economics. This is sometimes referred to as the opportunity cost thesis, which states that when incomes are low and expected returns from fighting outweigh the benefits of traditional economic activity, one’s motivation to join a militia or rebellion increases. Researchers refer to this motivator as greed, a reference to the material benefits—even extreme wealth—often anticipated by groups staging rebellion. In the case of recruitment of food insecure populations to extremist movements, though, it is not one’s desire for wealth but one’s inability to meet their basic needs that is exploited. This is not greed, but desperation.

Or is it the world’s biggest opportunity for U.S. corporations, a honeypot that will enrich our firms and make us more prosperous as a result? Those are arguably the two biggest questions in the global economy right now. With the U.S. growing at a sluggish 2.5% and Europe doing even worse, all eyes are on China as the world’s growth engine. In the mere 30 years since its communist leadership exchanged Maoist rhetoric for good old capitalism–or what it calls “socialism with Chinese characteristics”–China has become the world’s second largest economy and the chief rival of the U.S. for global dominance. China’s 1.3 billion upwardly mobile people are voracious consumers of everything from cars to smartphones to Kentucky Fried Chicken. Through its relentless exports, China has amassed a mountain of cash reserves and made itself Washington’s biggest foreign creditor. However, the country that vacuumed up factories to become the Workshop of the World is fading into history. China is a victim of its own success. Decades of nonstop growth have forever altered its place in the global economy and changed how it must compete with rich nations like the U.S. and emerging economies like India. The tools that China has used to spark its economic miracle–government support, cheap labor, state-directed finance–cannot ensure its future. The country can no longer rely on just making lots of stuff; China has to invent things, design them, brand them and market them. Instead of following the leaders of global industry, China has to produce leaders of its own. Such a transition is not easy. Few emerging nations in modern times have made the leap from assembler to inventor, copycat to innovator. For China, this would mean an overhaul of its economy. Many of the products China manufactures today aren’t really Chinese at all. Apple iPads might be exported from assembly lines based in China, but the Chinese themselves do little more than piece them together. The core technologies come from elsewhere, and even the factories are run by foreign firms (like Taiwan’s Foxconn). For Chinese companies to compete with the world’s best, they will have to create products of their own that have an impact similar to the iPad’s. That requires a set of skills and know-how they don’t yet possess and a level of managerial expertise they haven’t yet developed. Economist William Janeway, author of the book Doing Capitalism in the Innovation Economy, says what has gotten China this far won’t be enough for the next step: “It is hard to start the process of pushing the frontier with [such] practices and policies.”

National Recycling Strategy: EPA published the  November 2021 and reaffirmed the goal to increase the U.S. recycling rate to 50 percent by 2030.  The Strategy identifies strategic objectives and actions needed to create a stronger, more resilient, and cost-effective U.S. municipal solid waste recycling system.  Recycling has been an important component of the EPA’s decades-long efforts to implement the Resource Conservation and Recovery Act (RCRA) and more recent efforts to pursue a Sustainable Materials Management (SMM) approach, which aims to reduce the environmental impacts of materials across their lifecycle.

Sustainable Materials Management (SMM) program: EPA releases an annual report, Advancing Sustainable Materials Management:  Facts and Figures, to provide information on Municipal Solid Waste (MSW) generation, recycling, composting, combustion with energy recovery and landfilling.  The report analyzes MSW trends in generation and management, materials and products, and economic indicators affecting MSW.

The present-day harsh environmental conditions influence the sustainable potentiality of plant system adversely. The projected average rise in global temperature from 2.0 to 4.9 °C by the year 2100 will expose plants to high heat waves situation during their entire life cycle. It has been predicted that in the near future at the global level, the combination of drought, salt stress, and extreme temperature stresses may lead to a drastic effect on plants’ fitness and their overall productivity. It has also been projected that about 90% of arable lands are prone to a single or multiple stress condition. A large number of plant functions and products are affected by climate variables with consequent changes in quality. Moreover, environmental pollution due to heavy metals has also affected the global as well as regional soil fertility, soil biomass, rhizosphere/soil health, and plant yields, leading to bioaccumulation of metals in the human food chain. The nutrient management in food crops and other higher plants is a key challenge as it relies mainly on traditional chemical fertilizers, although they are costly, bulky, and harmful to human food chain and the environment. In this regard, the use of nano-biofertilizers can prove much advantageous and eco-friendly. Overall, under adverse conditions, plants are forced to adapt to environmental harshness and combat the ecological/environmental changes responsible for altering their physiological, metabolic, and molecular functions. In this connection, plant hormones act alone or interacting with other hormones, generate multiple signals, and regulate the growth and development of plant organs. They also protect and improve the physical development of plants even under harsh environmental conditions such as water scarcity, soil salinity, temperature variation, and metal toxicity. Thus, understanding environmental stress signal sensing and the balance between defense and development in plants lays the foundation for improvement in plant resilience. This chapter highlights some of the recent advances in our understanding of the harsh environment and the potential of resilient plants to withstand the extreme environmental conditions.

By now, most of us have heard that the use of plastics is a big issue for the environment. Partly fuelled by the success of the , people are more aware than ever before about the – as well as the impact it can have on – with industries promising .

Single use plastics are now high on the agenda – with many people trying to do their bit to reduce usage. But what if all of this just provides a convenient distraction from some of the more serious environmental issues? In our we argue plastic pollution – or more accurately the response of governments and industry to addressing plastic pollution – provides a “convenient truth” that such as climate change.

So finds a new study from researchers at Sweden’s Chalmers University of Technology.1 Published this month in the scientific journal mBIO, it found  is giving rise to a growing number of microbes that produce pollution-fighting enzymes. The enzymes, which can degrade various types of plastic, appear to be evolving in direct response to the accumulation of plastic pollution, the quantity of which has increased from approximately 2 million tons per year 70 years ago to approximately 380 million tons per year today.1

“We found multiple lines of evidence supporting the fact that the global microbiome’s plastic-degrading potential correlates strongly with measurements of environmental plastic pollution — a significant demonstration of how the environment is responding to the pressures we are placing on it,” Aleksej Zelezniak, associate professor of systems biology at the Chalmers University of Technology, said in a .

UC Riverside environmental engineering team has discovered specific bacterial species that can destroy certain kinds of "forever chemicals," a step further toward low-cost treatments of contaminated drinking water sources.

The microorganisms belong to the genus Acetobacterium and they are commonly found in wastewater environments throughout the world.