Technology
Artificial intelligence
About AI: A brief introduction
Artificial intelligence (AI) might sound like something from a science fiction movie in which robots are ready to take over the world. While such robots are purely fixtures of science fiction (at least for now), AI is already part of our daily lives, whether we know it or not.
Think of your Google inbox: Some of the emails you receive end up in your spam folder, while others are marked as ‘social’ or ‘promotion’. How does this happen? Google uses AI algorithms to automatically filter and sort e-mails by categories. These algorithms can be seen as small programs that are trained to recognise certain elements within an email that make it likely to be a spam message, for example. When the algorithm identifies one or several of those elements, it marks the email as spam and sends it to your spam folder. Of course, algorithms do not work perfectly, but they are continuously improved. When you find a legitimate email in your spam folder, you can tell Google that it was wrongly marked as spam. Google uses that information to improve how its algorithms work.
AI is widely used in internet services: Search engines use AI to provide better search results; social media platforms rely on AI to automatically detect hate speech and other forms of harmful content; and, online stores use AI to suggest products you are likely interested in based on your previous shopping habits. More complex forms of AI are used in manufacturing, transportation, agriculture, healthcare, and many other areas. Self-driving cars, programs able to recognise certain medical conditions with the accuracy of a doctor, systems developed to track and predict the impact of weather conditions on crops – they all rely on AI technologies.
As the name suggests, AI systems are embedded with some level of ‘intelligence’ which makes them capable to perform certain tasks or replicate certain specific behaviours that normally require human intelligence. What makes them ‘intelligent’ is a combination of data and algorithms. Let’s look at an example which involves a technique called machine learning. Imagine a program able to recognise cars among millions of images. First of all, that program is fed with a high number of car images. Algorithms then ‘study’ those images to discover patterns, and in particular the specific elements that characterise the image of a car. Through machine learning, algorithms ‘learn’ what a car looks like. Later on, when they are presented with millions of different images, they are able to identify the images that contain a car. This is, of course, a simplified example – there are far more complex AI systems out there. But basically all of them involve some level of initial training data and an algorithm which learns from that data in order to be able to perform a task.
Some AI systems go beyond this, by being able to learn from themselves and improve themselves. One famous example is DeepMind’s AlphaGo Zero: The program initially only knows the rules of the Go game; however, it then plays the game with itself and learns from its successes and failures to become better and better.
Going back to where we started: Is AI really able to match human intelligence? In specific cases – like playing the game of Go – the answer is ‘yes’. That being said, what has been coined as ‘artificial general intelligence’ (AGI) – advanced AI systems that can replicate human intellectual capabilities in order to perform complex and combined tasks – does not yet exist. Experts have divided opinions on whether AGI is something we will see in the near future, but it is certain that scientists and tech companies will continue to develop more and more complex AI systems.
The policy implications of AI
Applying AI for social good is a principle that many tech companies have adhered to. They see AI as a tool that can help address some of the world’s most pressing problems, in areas such as climate change and disease eradication. The technology and its many applications certainly carry significant potential for good, but there are also risks. Accordingly, the policy implications of AI advancements are far‐reaching. While AI can generate economic growth, there are growing concerns over the significant disruptions it could bring to the labour market. Issues related to privacy, safety, and security are also in focus.
As innovations in the field continue, more and more AI standards and AI governance frameworks are being developed to help ensure that AI applications have minimal unintended consequences.
Social and economic
AI has significant potential to stimulate economic growth and contribute to sustainable development. But it also comes with disruptions and challenges.
Safety and security
AI applications bring into focus issues related to cybersecurity (from cybersecurity risks specific to AI systems to AI applications in cybersecurity), human safety, and national security.
Human rights
The uptake of AI raises profound implications for privacy and data protection, freedom of expression, freedom of assembly, non-discrimination, and other human rights and freedoms.
Ethical concerns
The involvement of AI algorithms in judgments and decision-making gives rise to concerns about ethics, fairness, justice, transparency, and accountability.
Governing AI
When debates on AI governance first emerged, one overarching question was whether AI-related challenges (in areas such as safety, privacy, and ethics) call for new legal and regulatory frameworks, or whether existing ones could be adapted to also cover AI.
Applying and adapting existing regulation was seen by many as the most suitable approach. But as AI innovation accelerated and applications became more and more pervasive, AI-specific governance and regulatory initiatives started emerging at national, regional, and international levels.
USA Bill of Rights
The Blueprint for an AI Bill of Rights is a guide for a society that protects people from AI threats and uses technologies in ways that reinforce our highest values. Responding to the experiences of the American public, and informed by insights from researchers, technologists, advocates, journalists, and policymakers, this framework is accompanied by From Principles to Practice—a handbook for anyone seeking to incorporate these protections into policy and practice, including detailed steps toward actualising these principles in the technological design process.
China’s Interim Measures for Generative Artificial Intelligence
Released in July 2023 and applicable starting 15 August 2023, the measures apply to ‘the use of generative AI to provide services for generating text, pictures, audio, video, and other content to the public in the People’s Republic of China’. The regulation covers issues related to intellectual property rights, data protection, transparency, and data labelling, among others.
EU’s AI Act
Proposed by the European Commission in April 2021, the EU AI Act was formally adopted by the European Council on 21 May 2024, and came into effect on 1 August of the same year. The AI regulation introduces a risk-based regulatory approach for AI systems: if an AI system poses exceptional risks, it is banned; if an AI system comes with high risks (for instance, the use of AI in performing surgeries), it will be strictly regulated; if an AI system only involves limited risks, focus is placed on ensuring transparency for end users.
UNESCO Recommendation on AI Ethics
Adopted by UNESCO member states in November 2021, the recommendation outlines a series of values, principles, and actions to guide states in the formulation of their legislation, policies, and other instruments regarding AI. For instance, the document calls for action to guarantee individuals more privacy and data protection, by ensuring transparency, agency, and control over their personal data. Explicit bans on the use of AI systems for social scoring and mass surveillance are also highlighted, and there are provisions for ensuring that real-world biases are not replicated online.
OECD Recommendation on AI
Adopted by the OECD Council in May 2019, the recommendation encourages countries to promote and implement a series of principles for responsible stewardship of trustworthy AI, from inclusive growth and human-centred values to transparency, security, and accountability. Governments are further encouraged to invest in AI research and development, foster digital ecosystems for AI, shape enabling policy environments, build human capacities, and engage in international cooperation for trustworthy AI.
Council of Europe work on a Convention on AI and human rights
In 2021 the Committee of Ministers of the Council of Europe (CoE) approved the creation of a Committee on Artificial Intelligence (CAI) tasked with elaborating a legal instrument on the development, design, and application of AI systems based on the CoE’s standards on human rights, democracy and the rule of law, and conducive to innovation. On 17 May 2024, the Committee of Ministers adopted the Framework Convention on AI, Human Rights, Democracy and the Rule of Law. The Convention will be opened for signature on 5 September 2024.
Group of Governmental Experts on Lethal Autonomous Weapons Systems
Within the UN System, the High Contracting Parties to the Convention on Certain Conventional Weapons (CCW) established a Group of Governmental Experts on emerging technologies in the area of lethal autonomous weapons systems (LAWS) to explore the technical, military, legal, and ethical implications of LAWS. The group has been convened on an annual basis since its creation. In 2019, it agreed on a series of Guiding principles, which, among other issues, confirmed the application of international humanitarian law to the potential development and use of LAWS, and highlighted that human responsibility must be retained for decisions on the use of weapons systems.
Global Partnership on Artificial Intelligence
Launched in June 2020 and counting 29 members in 2024, the Global Partnership on Artificial Intelligence (GPAI) is a multistakeholder initiative dedicated to ‘sharing multidisciplinary research and identifying key issues among AI practitioners, with the objective of facilitating international collaboration, reducing duplication, acting as a global reference point for specific AI issues, and ultimately promoting trust in and the adoption of trustworthy AI’.
(AU) Continental AI Strategy
Adopted by the African Union Executive Council on July 18-19, 2024, the AI Strategy advocates for unified national approaches among AU member states to navigate the complexities of AI-driven transformation. It seeks to enhance regional and global cooperation, positioning Africa as a leader in inclusive and responsible AI development. The Continental AI Strategy emphasizes a people-centric, development-oriented, and inclusive approach, structured around five key focus areas and fifteen policy recommendations.
National AI strategies
As AI technologies continue to evolve at a fast pace and have more and more applications in various areas, countries are increasingly aware that they need to keep up with this evolution and to take advantage of it. Many are developing national AI development strategies, as well as addressing the economic, social, and ethical implications of AI advancements. China, for example, released a national AI development plan in 2017, intended to help make the country the world leader in AI by 2030 and build a national AI industry worth of US$150 billion. In the United Arab Emirates (UAE), the adoption of a national AI strategy was complemented by the appointment of a State Minister for AI to work on ‘making the UAE the world’s best prepared [country] for AI and other advanced technologies’. Canada, France, Germany and Mauritius were among the first countries to launch national AI strategies. These are only a few examples; there are many more countries that have adopted or are working on such plans and strategies, as the map below shows.
Last updated: June 2024
AI on the international level
The Council of Europe, the EU, OECD, and UNESCO are not the only international spaces where AI-related issues are discussed; the technology and its policy implications are now featured on the agenda of a wide range of international organisations and processes. Technical standards for AI are being developed at ITU, the ISO, the IEC, and other standard-setting bodies. ITU is also hosting an annual AI for Good summit exploring the use of AI to accelerate progress towards sustainable development. UNICEF has begun working on using AI to realise and uphold children’s rights, while the International Labour Organization (ILO) is looking at the impact of AI automation on the world of work. The World Intellectual Property Organization (WIPO) is discussing intellectual property issues related to the development of AI, the World Health Organization (WHO) looks at the applications and implications of AI in healthcare, and the World Meteorological Organization (WMO) has been using AI in weather forecast, natural hazard management, and disaster risk reduction.
As discussions on digital cooperation have advanced at the UN level, AI has been one of the topics addressed within this framework. The 2019 report of the UN High-Level Panel on Digital Cooperation tackles issues such as the impact of AI on labour markets, AI and human rights, and the impact of the misuse of AI on trust and social cohesion. The UN Secretary-General’s Roadmap on Digital Cooperation, issued in 2020, identifies gaps in international coordination, cooperation, and governance when it comes to AI. The Our Common Agenda report released by the Secretary-General in 2021 proposes the development of a Global Digital Compact (with principles for ‘an open, free and secure digital future for all’) which could, among other elements, promote the regulation of AI ‘to ensure that it is aligned with shared global values’.
AI and its governance dimensions have featured high on the agenda of bilateral and multilateral processes such as the EU-US Trade and Technology Council, G7, G20, and BRICS. Regional organisations such as the African Union (AU), the Association of Southeast Asian Nations (ASEAN), and the Organization of American States (OAS) are also paying increasing attention to leveraging the potential of AI for economic growth and sustainable development.
In recent years, annual meetings of the Internet Governance Forum (IGF) have featured AI among their main themes.
More on the policy implications of AI
The economic and social implications of AI
AI has significant potential to stimulate economic growth. In production processes, AI systems increase automation, and make processes smarter, faster, and cheaper, and therefore bring savings and increased efficiency. AI can improve the efficiency and the quality of existing products and services, and can also generate new ones, thus leading to the creation of new markets. It is estimated that the AI industry could contribute up to US$15.7 trillion to the global economy by 2030. Beyond the economic potential, AI can also contribute to achieving sustainable development goals (SDGs); for instance, AI can be used to detect water service lines containing hazardous substances (SDG 6 – clean water and sanitation), to optimise the supply and consumption of energy (SDG 7 – affordable and clean energy), and to analyse climate change data and generate climate modelling, helping to predict and prepare for disasters (SDG 13 – climate action). Across the private sector, companies have been launching programmes dedicated to fostering the role of AI in achieving sustainable development. Examples include IBM’s Social Science for Good, Google’s AI for Social Good, and Microsoft’s AI for Good projects.
For this potential to be fully realised, there is a need to ensure that the economic benefits of AI are broadly shared at a societal level, and that the possible negative implications are adequately addressed. The 2022 edition of the Government AI Readiness Index warns that ‘care needs to be taken to make sure that AI systems don’t just entrench old inequalities or disenfranchise people. In a global recession, these risks are evermore important.’ One significant risk is that of a new form of global digital divide, in which some countries reap the benefits of AI, while others are left behind. Estimates for 2030 show that North America and China will likely experience the largest economic gains from AI, while developing countries – with lower rates of AI adoption – will register only modest economic increases.
The disruptions that AI systems could bring to the labour market are another source of concern. Many studies estimate that automated systems will make some jobs obsolete, and lead to unemployment. Such concerns have led to discussions about the introduction of a ‘universal basic income’ that would compensate individuals for disruptions brought on the labour market by robots and by other AI systems. There are, however, also opposing views, according to which AI advancements will generate new jobs, which will compensate for those lost without affecting the overall employment rates. One point on which there is broad agreement is the need to better adapt the education and training systems to the new requirements of the jobs market. This entails not only preparing the new generations, but also allowing the current workforce to re-skill and up-skill itself.
AI, safety, and security
AI applications in the physical world (e.g. in transportation) bring into focus issues related to human safety, and the need to design systems that can properly react to unforeseen situations with minimal unintended consequences. Beyond self-driving cars, the (potential) development of other autonomous systems – such as lethal autonomous weapons systems – has sparked additional and intense debates on their implications for human safety.
AI also has implications in the cybersecurity field. In addition to the cybersecurity risks associated with AI systems (e.g. as AI is increasingly embedded in critical systems, they need to be secured to potential cyberattacks), the technology has a dual function: it can be used as a tool to both commit and prevent cybercrime and other forms of cyberattacks. As the possibility of using AI to assist in cyberattacks grows, so does the integration of this technology into cybersecurity strategies. The same characteristics that make AI a powerful tool to perpetrate attacks also help to defend against them, raising hopes for levelling the playing field between attackers and cybersecurity experts.
Going a step further, AI is also looked at from the perspective of national security. The US Intelligence Community, for example, has included AI among the areas that could generate national security concerns, especially due to its potential applications in warfare and cyber defense, and its implications for national economic competitiveness.
AI and human rights
AI systems work with enormous amounts of data, and this raises concerns regarding privacy and data protection. Online services such as social media platforms, e-commerce stores, and multimedia content providers collect information about users’ online habits, and use AI techniques such as machine learning to analyse the data and to ‘improve the user’s experience’ (for example, Netflix suggests movies you might want to watch based on movies you have already seen). AI-powered products such as smart speakers also involve the processing of user data, some of it of personal nature. Facial recognition technologies embedded in public street cameras have direct privacy implications.
How is all of this data processed? Who has access to it and under what conditions? Are users even aware that their data is extensively used? These are only some of the questions generated by the increased use of personal data in the context of AI applications. What solutions are there to ensure that AI advancements do not come at the expense of user privacy? Strong privacy and data protection regulations (including in terms of enforcement), enhanced transparency and accountability for tech companies, and embedding privacy and data protection guarantees into AI applications during the design phase are some possible answers.
Algorithms, which power AI systems, could also have consequences on other human rights. For example, AI tools aimed at automatically detecting and removing hate speech from online platforms could negatively affect freedom of expression: Even when such tools are trained on significant amounts of data, the algorithms could wrongly identify a text as hate speech. Complex algorithms and human-biassed big data sets can serve to reinforce and amplify discrimination, especially among those who are disadvantaged.
Ethical concerns
As AI algorithms involve judgements and decision-making – replicating similar human processes – concerns are being raised regarding ethics, fairness, justice, transparency, and accountability. The risk of discrimination and bias in decisions made by or with the help of AI systems is one such concern, as illustrated in the debate over facial recognition technology (FRT). Several studies have shown that FRT programs present racial and gender biases, as the algorithms involved are largely trained on photos of males and white people. If law enforcement agencies rely on such technologies, this could lead to biassed and discriminatory decisions, including false arrests.
One way of addressing concerns over AI ethics could be to combine ethical training for technologists (encouraging them to prioritise ethical considerations when creating AI systems) with the development of technical methods for designing AI systems in a way that they can avoid such risks (i.e. fairness, transparency, and accountability by design). The Institute of Electrical and Electronics Engineers’ Global Initiative for Ethical Considerations in Artificial Intelligence and Autonomous Systems is one example of initiatives that are aimed at ensuring that technologists are educated, trained, and empowered to prioritise ethical considerations in the design and development of intelligent systems.
Researchers are carefully exploring the ethical challenges posed by AI and are working, for example, on the development of AI algorithms that can ‘explain themselves’. Being able to better understand how an algorithm makes a certain decision could also help improve that algorithm.
AI and other digital technologies and infrastructures
Telecom infrastructure
AI is used to optimise network performance, conduct predictive maintenance, dynamically allocate network resources, and improve customer experience, among others.
Internet of things
The interplay between AI and IoT can be seen in multiple applications, from smart home devices and vehicle autopilot systems to drones and smart cities applications.
Semiconductors
AI algorithms are used in the design of chips, for improved performance and power efficiency, for instance. And then semiconductors themselves are used in AI hardware and research.
Quantum computing
Although largely still a field of research, quantum computing promises enhanced computational power which, coupled with AI, can help address complex problems.
Other advanced technologies
AI techniques are increasingly used in the research and development of other emerging and advanced technologies, from 3D printing and virtual reality, to biotechnology and synthetic biology.
Science & Environment
What caused the hydrothermal explosion at Yellowstone National Park? A meteorologist explains
Yellowstone National Park visitors were sent running and screaming Tuesday when a hydrothermal explosion spewed boiling hot water and rocks into the air. No one was injured, but it has left some wondering: How does this happen and why wasn’t there any warning?
The Weather Channel’s Stephanie Abrams said explosions like this are caused by underground channels of hot water, which also create Yellowstone’s iconic geysers and hot springs.
“When the pressure rapidly drops in a localized spot, it actually forces the hot water to quickly turn to steam, triggering a hydrothermal explosion since gas takes up more space than liquid,” Abrams said Wednesday on “CBS Mornings.” “And this explosion can rupture the surface, sending mud and debris thousands of feet up and more than half a mile out in the most extreme cases.”
Tuesday’s explosion was not that big, Abrams said, “but a massive amount of rocks and dirt buried the Biscuit Basin,” where the explosion occurred.
A nearby boardwalk was left with a broken fence and was covered in debris. Nearby trees were also killed, with the U.S. Geological Survey saying the plants “can’t stand thermal activity.”
“Because areas heat up and cool down over time, trees will sometimes die out when an area heats up, regrow as it cools down, but then die again when it heats up,” the agency said on X.
The USGS said it considers this explosion small, and that similar explosions happen in the national park “perhaps a couple times a year.” Often, though, they happen in the backcountry and aren’t noticed.
“It was small compared to what Yellowstone is capable of,” USGS Volcanoes said on X. “That’s not to say it was not dramatic or very hazardous — obviously it was. But the big ones leave craters hundreds of feet across.”
The agency also said that “hydrothermal explosions, “being episodes of water suddenly flashing to steam, are notoriously hard to predict” and “may not give warning signs at all.” It likened the eruptions to a pressure cooker.
While Yellowstone sits on a dormant volcano, officials said the explosion was not related to volcanic activity.
“This was an isolated incident in the shallow hot-water system beneath Biscuit Basin,” the USGS said. “It was not triggered by any volcanic activity.”
Technology
What happened to the Metaverse?
S6
Ep135
What happened to the Metaverse?
Host Andrew Davidson is joined by technology experts Brian Benway and Jan Urbanek in a discussion about the Metaverse. Our experts shed light on the latest technological and hardware advancements and marketing strategies from Big Tech. What will it take for the Metaverse to gain mainstream popularity? Listen now to find out!
Head over to Mintel’s LinkedIn to let us know what you think of today’s episode, and visit mintel.com to become a member of our free Spotlight community.
Visit the Mintel Store to explore all our technology research and buy a report today.
Meet the Host
Andrew Davidson
SVP/Chief Insights Officer, Mintel Comperemedia.
Meet the Guests
Brian Benway
Senior Analyst, Gaming and Entertainment, Mintel Reports US.
Jan Urbanek
Senior Analyst, Consumer Technology, Mintel Reports Germany.
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For the latest in consumer and industry news, top trends and market perspectives, stay tuned to Mintel News featuring commentary from Mintel’s team of global category analysts.
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Science & Environment
Archaeologists make stunning underwater discovery of ancient mosaic in sea off Italy
Researchers studying an underwater city in Italy say they have found an ancient mosaic floor that was once the base of a Roman villa, a discovery that the local mayor called “stupendous.”
The discovery was made in Bay Sommersa, a marine-protected area and UNESCO World Heritage Site off the northern coast of the Gulf of Naples. The area was once the Roman city of Baia, but it has become submerged over the centuries thanks to volcanic activity in the area. The underwater structures remain somewhat intact, allowing researchers to make discoveries like the mosaic floor.
The Campi Flegrei Archaeological Park announced the latest discovery, which includes “thousands of marble slabs” in “hundreds of different shapes,” on social media.
“This marble floor has been at the center of the largest underwater restoration work,” the park said, calling the research “a new challenge” and made “very complicated due to the extreme fragment of the remains and their large expansion.”
The marble floor is made of recovered, second-hand marble that had previously been used to decorate other floors or walls, the park said. Each piece of marble was sharpened into a square and inscribed with circles. The floor is likely from the third century A.D., the park said in another post, citing the style of the room and the repurposing of the materials as practices that were common during that time.
Researchers are working carefully to extract the marble pieces from the site, the park said. The recovery work will require careful digging around collapsed walls and other fragmented slabs, but researchers hope to “be able to save some of the geometries.”
Once recovered, the slabs are being brought to land and cleaned in freshwater tanks. The marble pieces are then being studied “slab by slab” to try to recreate the former mosaic, the park said.
“The work is still long and complex, but we are sure that it will offer many prompts and great satisfactions,” the park said.
Technology
SpaceX fires up Starship engines ahead of fifth test flight
SpaceX has just performed a static fire of the six engines on its Starship spacecraft as it awaits permission from the Federal Aviation Administration (FAA) for the fifth test flight of the world’s most powerful rocket.
The Elon Musk-led spaceflight company shared footage and an image of the test fire on X (formerly Twitter) on Thursday. It shows the engines firing up while the vehicle remained on the ground.
Six engine static fire of Flight 6 Starship pic.twitter.com/fzJz9BWBn6
— SpaceX (@SpaceX) September 19, 2024
For flights, the Starship spacecraft is carried to orbit by the first-stage Super Heavy booster, which pumps out 17 million pounds of thrust at launch, making it the most powerful rocket ever built.
The Super Heavy booster and Starship spacecraft — collectively known as the Starship — have launched four times to date, with the performance of each test flight showing improvements over the previous one.
The first one, for example, exploded shortly after lift off from SpaceX’s Starbase facility in Boca Chica, Texas, in April last year, while the second effort, which took place seven months later, achieved stage separation before an explosion occurred — an incident that was captured in dramatic footage. The third and fourth flights lasted much longer and achieved many of the mission objectives, including getting the Starship spacecraft to orbit.
The fifth test flight isn’t likely to take place until November at the earliest, according to a recent report. It will involve the first attempt to use giant mechanical arms to “catch” the Super Heavy booster as it returns to the launch area. SpaceX recently expressed extreme disappointment at the time that it’s taking the FAA to complete an investigation that will pave the way for the fifth Starship test, and has said that it’ll be ready to launch the vehicle within days of getting permission from the FAA.
Once testing is complete, NASA wants to use the Starship, along with its own Space Launch System rocket, to launch crew and cargo to the moon and quite possibly for destinations much further into space such as Mars. NASA is already planning to use a modified version of the Starship spacecraft to land the first astronauts in five decades on the lunar surface in the Artemis III mission, currently set for 2026.
Science & Environment
Painkiller used in cattle wiped out India’s vultures, and scientists say that led to 500,000 human deaths
New Delhi — Scientists say Indian farmers’ eager uptake of a painkiller for their cattle in the 1990s has led to the inadvertent deaths of half of a million people and massive economic losses — not from any harm to the cattle, but from the loss of millions of vultures, scavengers that historically devoured animals’ remains before they could rot and become vectors for disease.
In early 1990s, the patent on a painkiller called diclofenac lifted, making it cheap and widely available for India’s massive agricultural sector. Farmers use it to treat a wide array of conditions in cattle. But even a small amount of the drug is fatal to vultures. Since the beginning of its widespread use in India, the domestic vulture population has dropped from a whopping 50 million to just a few thousand — and according to a study published by the American Economic Association, the impact on humans has been monumental, reflecting the vital role the scavengers play.
Vultures have been a crucial part of India’s ecosystems for centuries. According to the authors of the study, entitled “The Social Costs of Keystone Species Collapse: Evidence From The Decline of Vultures in India,” the large, homely birds are a “keystone species” — one that plays an irreplaceable role in an ecosystem.
They’re the only scavengers that feed entirely on carcasses, and they do it extremely efficiently, quickly devouring the remains and leaving little behind to spread disease. The study authors say India’s vultures would typically eat at least 50 million animal carcasses every year, before their population was decimated.
In doing so, they prevented the dead farm animals from rotting, and the deadly bacteria and other pathogens that thrive in carcasses from being transmitted into human populations.
“In a country like India with prohibitions on eating beef, most cattle end up turning into carcasses,” Anant Sudarshan, an associate professor of economics at the University of Warwick in England, who co-authored the study, told CBS News. “Vultures provide an incredible disposal service for free. … A group of vultures takes about 45 minutes to turn a cow carcass into bone.”
The vultures’ keen appetite also helped keep the populations of competing scavengers in check, such as feral dogs and rats, which can transmit rabies and a host of other diseases.
In 1994, farmers began giving diclofenac to their cattle and other livestock. The drug causes kidney failure and death in vultures that feed on the carcasses of animals given the painkiller, and the population of the birds shrank from 50 million to just 20,000 over the course of the ensuing decade alone.
Without the vultures around to do the job, farmers started disposing their dead livestock in local bodies of water, which caused water pollution — and another way for pathogens to reach humans.
Sudarshan and study co-author Eyal Frank, an environmental economist at the University of Chicago Harris School of Public Policy, examined the impact of the drastically reduced vulture population on human health by mapping vulture habitats with health data from more than 600 districts in India. They said their research shows 100,000 human deaths every year between 2000 and 2005 could be linked with the decreased vulture populations.
It also shows economic losses they estimated at $69 billion per year, largely associated with premature human deaths due to the collapse of the scavenger population.
These deaths were caused, according to their research, by the spread of diseases that a thriving vulture population would have mitigated. Stray dog populations, and with them, the spread of rabies, also increased during the timeframe, as did the amount of bacteria measured in many local water sources.
“India is now the largest center of rabies in the world, as the feral dog population has grown dramatically,” Sudarshan told CBS News.
Without a major vulture rebound, the study authors said the spread of disease and resulting deaths will only continue in the coming years, as will the costs associated with health care.
India did ban diclofenac for veterinary use in 2006, but Sudarshan said the ban needs to be enforced much more effectively. He and Eyal have called for more conservation funding to boost vulture populations, but they’ve warned that even if the Indian government does mount a major effort, it will take at least a decade for the species to bounce back to the extent required because they’re “slow reproducers.”
As an alternative to bringing the vultures back, Sudarshan said India could build a network of incinerators around the country, but the estimated cost of that is about $1 billion per year, and they would use a huge amount of energy and create considerable air pollution, which is already a major problem for India.
“So, it makes more sense to bring back the natural way of dealing with the millions of animal carcasses that India produces each year,” he said.
And he said that work must start urgently, as the “vultures began dying in the 1990s. India has not done anything three decades on.”
The government does spend about $3 million per year to save India’s native tigers. Sudarshan said while vultures may be far less of a tourist attraction, there’s a broader question about “the basis of our conservation policy.”
“Our paper shows that the cost of losing them [vultures] is about $69 billion a year, which is far higher than any benefits the tiger” brings, he said, adding: “We need to think from a cost effectiveness point of view and growth view, how should we pick species to conserve?”
“Understanding the role vultures play in human health underscores the importance of protecting wildlife – and not just the cute and cuddly,” said his co-author, Frank. “They all have a job to do in our ecosystems that impacts our lives.”
Technology
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max
Apple has recently announced its new flagship smartphones, including the iPhone 16 Pro Max, the largest one. In this article, we’ll compare it to the best Samsung has to offer, the Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max. These two devices are quite different when it comes to design, but that’s not where the similarities end, not at all, quite the contrary, actually. There is plenty to talk about here.
As we usually do, we will first list the specifications of both smartphones and will then move to compare them across a number of other categories. We will compare their designs, displays, performance, battery life, cameras, and audio output. There are quite a few differences to talk about here, as the two companies have completely different approaches. Let’s get down to it, shall we?
Specs
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max, respectively
– Screen size:
6.9-inch Dynamic AMOLED 2X (flat, adaptive 120Hz, HDR10+, 2,600 nits max brightness)
6.9-inch LTPO Super Retina XDR OLED ( flat, 120Hz, HDR, 2,000 nits)
– Display resolution:
3120 x 1440
2868 x 1320
– SoC:
Qualcomm Snapdragon 8 Gen 3 for Galaxy (4nm)
Apple A18 Pro (3nm)
– RAM:
12GB (LPDDR5X)
16GB (LPDDR5X)
– Storage:
256GB/512GB/1TB (UFS 4.0)
128GB/256GB/512GB/1TB (UFS 3.1)
– Rear cameras:
200MP (wide, f/1.7 aperture, OIS, multi-directional PDAF, 0.6um pixel size), 12MP (ultrawide, 120-degree FoV, f/2.2 aperture, Dual Pixel PDAF 1.4um pixel size), 10MP (telephoto, f/2.4 aperture, OIS, Dual Pixel PDAF, 1.12um pixel size, 3x optical zoom), 50MP (periscope telephoto, OIS, PDAF, 5x optical zoom)
48MP (wide, f/1.8 aperture, 1/1.28-inch sensor, 1.22um pixel size, sensor-shift OIS), 48MP (ultrawide, f/2.2 aperture, 0.7um pixel size, PDAF), 12MP (periscope telephoto, f/2.8 aperture, 1/3.06-inch sensor, 1.12um pixel size, 3D sensor-shift OIS, 5x optical zoom).
– Front cameras:
12MP (wide, f/2.2 aperture, Dual Pixel PDAF, 22mm lens)
12MP (f/1.9 aperture, PDAF, 1/3.6-inch sensor size, OIS)
– Battery:
5,000mAh
Not confirmed yet
– Charging:
45W wired, 15W wireless, 4.5W reverse wireless (charger not included)
38W wired & 25W MagSafe & Qi2 wireless, 7.5W Qi wireless, 5W reverse wired
– Dimensions:
162.3 x 79 x 8.6mm
163 x 77.6 x 8.3 mm
– Weight:
232/233 grams
227 grams
– Connectivity:
5G, LTE, NFC, Wi-Fi, USB Type-C, Bluetooth 5.3
– Security:
Ultrasonic in-display fingerprint scanner & facial scanning
Face ID (3D facial scanning)
– OS:
Android 14 with One UI 6.1
iOS 18
– Price:
$1,299+
$1,199+
– Buy:
Samsung Galaxy S24 Ultra (Best Buy)
Apple iPhone 16 Pro Max
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max: Design
The moment you lay your eyes on the two phones you’ll realize how different they are. The Galaxy S24 Ultra has a flat top and bottom sides, but its left and right sides are curved. All sides of the iPhone 16 Pro Max are flat, though they are slightly rounded toward the edges. Apple did that so that the phone is more comfortable to hold. Both phones do include flat displays with cutouts on them. The Galaxy S24 Ultra has a little hole at the top of the display, while the iPhone 16 Pro Max has a rather large pill-shaped cutout.
The bezels around their displays are very thin, and uniform. All the physical buttons sit on the right-hand side of the Galaxy S24 Ultra. The iPhone 16 Pro Max has a power/lock key there and a Camera Control button. On the left, you’ll find the volume up and down buttons, and the Action Button. The two devices have considerably different camera setups on the back. Each of the Galaxy S24 Ultra’s four cameras protrudes directly from the back side. There is no dedicated camera island. The exact opposite is true for the iPhone 16 Pro Max. Its camera island sits in the top-left corner with three cameras.
Both of these phones are made out of titanium and glass. They have a titanium frame. They are both also IP68 certified for water and dust resistance. Corning’s Gorilla Armor sits on the back of Samsung’s handset. Apple’s device has a “Corning-made glass” on the back. The two phones are almost the same in terms of height, while the Galaxy S24 Ultra is slightly wider. They are almost identical in terms of thickness. Both phones are quite slippery, and the Galaxy S24 Ultra is 5 grams heavier.
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max: Display
The Galaxy S24 Ultra feautres a 6.8-inch QHD+ 3120 x 1440 Dynamic LTPO AMOLED 2X display. That panel has an adaptive refresh rate of up to 120Hz. It also offers support for HDR10+ content, and its peak brightness is at 2,600 nits. The screen-to-body ratio is around 88%, while the display aspect ratio is 19.5:9. The Gorilla Armor from Corning sits on top of the display in order to protect it.
The iPhone 16 Pro Max, on the flip side, has a 6.9-inch LTPO Super Retina XDR OLED display. That display has an adaptive refresh rate of up to 120Hz. HDR10 is supported, as is Dolby Vision. The peak brightness here is 2,000 nits. The screen-to-body ratio on the iPhone 16 Pro Max is around 91%. The display aspect ratio is 19.5:9. This display is protected by the Ceramic Shield glass.
Both of these panels are great. They are vivid, bright, and have great viewing angles. The blacks are deep, and the touch response is good. Neither phone has high-frequency PWM dimming, though. The Galaxy S24 Ultra does technically get brighter, but the difference is not that big, not even in direct sunlight. What the Galaxy S24 Ultra does have an advantage with is… glare. The Gorilla Armor on top of the display is unbelievable in that regard.
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max: Performance
The Snapdragon 8 Gen 3 for Galaxy fuels the Galaxy S24 Ultra. That is a 4nm chip and Qualcomm’s best one at the time of writing this. The phone is also equipped with 12GB of LPDDR5X RAM and UFS 4.0 flash storage. The iPhone 16 Pro Max is fueled by the Apple A18 Pro processor. That is a 3nm chip, by the way. The phone is also equipped with 8GB of RAM and NVMe flash storage. Neither phone offers expandable storage, by the way.
With that being said, both phones do offer great performance. Our iPhone 16 Pro (Max) review is not ready yet, but plenty of impressions are already there. In any case, both devices are very fluid in terms of day-to-day use. They can jump between apps without a problem, and getting them to slow down is a chore. They do great regardless of what you’re doing, even when it comes to a bit more advanced things such as video processing.
What about gaming, though? Well, they’re great in that regard too. Non-demanding games are, of course, not a problem, but the same goes for truly demanding titles too. Each of these two smartphones can run basically anything you can think of, and do it really well. Titles like Genshin Impact are not a problem at all. They will get warm, but not too much, and that won’t affect the gaming performance at all.
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max: Battery
There is a 5,000mAh battery included inside the Galaxy S24 Ultra. Apple still didn’t confirm what battery it used in the iPhone 16 Pro Max, though. It is tipped to be a 4,676mAh unit, but we’re still not 100% sure. Apple’s handsets usually have smaller batteries compared to their Android counterparts, due to the way iOS operates, but that doesn’t mean they have inferior battery life. In fact, both of these smartphones are outstanding in that regard.
We were in awe of the Galaxy S24 Ultra’s battery life when we first reviewed it. The iPhone 16 Pro Max is showing a similar promise, actually. Getting to over 7-8 hours of screen-on-time is a possibility on both phones, though your mileage may vary, of course. That will depend on a number of factors. The point is, we were unable to drain the battery life of either phone in a day. We could have done that with constant gaming, of course, but with general heavy use, no… that didn’t happen.
What about charging? Well, the Galaxy S24 Ultra supports 45W wired, 15W wireless, and 4.5W reverse wireless charging. The iPhone 16 Pro Max, on the other hand, supports 45W wired, 25W MagSafe wireless, 15W Qi2 wireless, 7.5W Qi wireless, and 5W reverse wired charging. Do note that neither smartphone comes with a charger in the retail box, however. All you’ll get is a cable.
Samsung Galaxy S24 Ultra vs Apple iPhone 16 Pro Max: Cameras
The Samsung Galaxy S24 Ultra comes with four cameras on the back, while Apple’s handset has three rear cameras. The Galaxy S24 Ultra includes a 200-megapixel main camera, a 12-megapixel ultrawide unit (120-degree FoV), a 10-megapixel telephoto unit (3x optical zoom), and a 50-megapixel periscope telephoto camera (5x optical zoom). The iPhone 16 Pro Max, on the other hand, has a 48-megapixel main camera, a 48-megapixel ultrawide unit, and a 12-megapixel periscope telephoto camera (5x optical zoom).
The main camera sensors on the two phones are similar in terms of size. Both devices do a really good job with photos, though the results are different. Samsung’s images still look more processed, although Apple has been heading more and more in that direction. Both phones like brightening up the shadows during the day, even though the Galaxy S24 Ultra’s images do end up looking a bit more contrasty. The iPhone 16 Pro Max was more reliable for us in terms of balanced photos, for what it’s worth, but the Galaxy S24 Ultra was not far off.
Both ultrawide cameras do a good job, and keep a similar color profile to the main shooters. The results are notably different, though, as are with the main cameras. Something similar can be said for the telephoto cameras. This was a tossup between the two setups, as it all depended on what distance we were capturing. At times we preferred shots from the iPhone, but it was mostly from Samsung. Both devices also do a good job in low light and love to brighten up scenes, though Samsung more than Apple. That goes for all three cameras, by the way. The iPhone 16 Pro Max easily wins the video comparison.
Audio
Both of these smartphones include stereo speakers, and they’re really good on both ends. They’re loud enough, and the sound output is detailed enough. We did not notice noticeable distortion or anything like that.
There is no audio jack on either phone, but you can use their Type-C ports to connect your wired headphones. Alternatively, Bluetooth 5.3 is on offer for wireless audio connections… on both smartphones.
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