Archive for the ‘Ai’ Category

How to future-proof your digital presence in the era of AI-powered … – Search Engine Land

Artificial intelligence (AI) is a well-known technology in SEO, as its been used by Google for years to power its search engine.

Recently, major companies like Google, Bing, Adobe, Meta, and Apple have recognized the changing consumer behavior and started embracing AI as a central focus.

AI and machine learning (ML) now play a vital role in their core product offerings.

This article covers tips for safeguarding your digital presence in the face of AIs rapid evolution.

AI has revolutionized consumer-business interactions, providing a smooth experience and transforming how customers engage with companies.

As search engines evolve into answer engines, it becomes crucial to comprehend customer needs, journeys, and expected search behaviors across all channels.

To future-proof your digital presence, you must deliver the experience your customers seek.

While AI will change how we do things in the future, the human element is still needed for the final output and quality.

Here are some use cases of AI in search marketing.

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As we explore the many incredible applications of AI, we must also understand what it takes to future-proof our digital presence.

A future-looking strategy involves understanding where large language models (LLMs) get their data and whether we can populate them where relevant.

This relates to discoverability. If the answers come from certain repositories, ensuring you are in them may make sense.

Brands need to start thinking about what users want to know about the business rather than providing information about themselves.

Focus on fully optimizing your digital presence with images, reviews, products, schema, and Google Business Profile (GBP) categories.

A short video is also increasingly crucial because video, reviews, images, and GBP are prioritized in local pack results.

Similarly, helpful and relevant localized content with high authority for the time being can help maintain SERP visibility and remain vigilant about the evolving SERP.

Google is prioritizing informational, navigational, local, and nearby search queries to generate search generative experience (SGE) results across all types of searches, including organic, local/maps, images, news, videos, events, and conversation/voice search (how-to content and FAQs).

SGE results quickly surfaced if informational content from the brand domain is easily discovered and has high engagement and relevancy to the query.

The SERP results below show how easily discovered information-rich content is doing well.

Here are tips to future-proof your digital presence and establish a rock-solid plan to stay ahead as a business.

Ensure your content is created by keeping an entity-first strategy in mind.

I have written several articles about what entity search is, why it is topical, your competitive advantage, how it works, and the steps to deploy.

Ensure all types of content, such as images, videos, FAQs, etc. use proper schema architecture.

Your CMS, technical infrastructure, server and website architecture, and hosting environment should allow easy content discovery.

The site structure should be relatively flat and connect similar topics and subtopics through navigation.

Images, how-to content, web stories, recipes, knowledge graphs, FAQs, videos, maps, and events take up a portion of SERPs in SGE.

Let's ensure the content we create includes these and that schemas are properly nested for easy discovery.

As Google prioritizes mobile indexing over desktop indexing, it is essential to have a strategy to saturate mobile SERPs.

This includes using web stories, having a responsive mobile site that quickly loads on mobile devices, providing a seamless experience across various screen sizes and browsers, and delivering a secure and safe website.

To optimize images for quality, relevancy and experience, centralize all your assets (images, video, PDFs) using cloud storage and use AI/LLM models to rate the most critical metrics.

Ensure all your assets are surfaced right from a central place. Put lifestyle graphics in noindex folders to avoid wasting the crawl budget.

Only the most relevant qualitative image with entity data must be discoverable.

As AI becomes front and center, it is about saturating SERPs, zero clicks, impressions, time on the site, and reduction in bouse rate.

Other qualitative metrics will be site speed, time spent on the site, click and interactions with various assets and features on the website.

Leverage customer data and analytics to personalize user experience.

Personalization enhances user engagement, conversion rates, and overall customer satisfaction. It ultimately increases your authority and trust factor.

Search marketers must harness skills to use AI effectively.

Future-proofing your digital presence means enabling your team with the right tools and skills to create a strategic plan, incorporate AI, and understand the customer journey and the channels to leverage data to personalize the experience.

Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.

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Schumer says lawmakers starting from scratch on AI regulation – The Hill

Senate Majority Leader Chuck Schumer (D-N.Y.) said lawmakers will be “starting from scratch” on figuring out how to regulate the new wave of artificial intelligence (AI) in the U.S. 

In a speech during a Center for Strategic & International Studies (CSIS) event Tuesday, Schumer said lawmakers have no choice but to acknowledge the coming changes with AI, noting that many “want to ignore” necessary regulations due to the complexity of the new technology. 

“AI is unlike anything Congress has dealt with before,” Schumer said in his speech. 

“It’s not like labor or health care or defense, where Congress has a long history we can work off of,” he added. “Experts are not even sure which questions policymakers should be asking. In many ways, we’re starting from scratch.” 

Schumer added in his speech that Congress is up for the challenge to address AI usage in the country, noting a list of legislation that has passed in Congress in the last two years under his leadership. 

“Don’t count Congress out,” he quipped.

The New York senator said he plans to reveal the framework of his SAFE Innovation Act on Wednesday — a bill meant to protect, expand and harness the potential of the new technology. 

Lawmakers’ interest in AI comes as other companies have introduced services this year implementing the technology. Microsoft announced earlier this year that its new premium messaging service, Teams Premium, will be powered by Open AI’s ChatGPT program.

ChatGPT — a free tool launched in November — automatically generates humanlike responses to users’ queries in a way that is more advanced than previous technology. President Biden traveled to San Francisco to meet with AI experts and researchers Tuesday to discuss managing the risk of the new technology.

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Schumer says lawmakers starting from scratch on AI regulation - The Hill

AI can make healthcare more accurate, accessible, and sustainable – World Economic Forum

Emerging technologies such as artificial intelligence (AI) and machine learning are transforming nearly all industries, among them the healthcare industry, which accounts for 11% of global GDP or $9 trillion annually. From the development of drugs and vaccines, to improving medical diagnosis and treatment, such technologies are being used in all stages of the value chain, boosting efficiencies across the overall healthcare system.

As the World Economic Forum launches the 2023 cohort of Technology Pioneers, we asked the six selectees how such emerging technologies are changing global health outcomes. Here is what they said:

Riddhiman Das, Chief Executive Officer, Tripleblind

Emerging technologies like AI and machine learning will revolutionize global health outcomes. These advancements can improve medical diagnosis, treatment and healthcare delivery. AI algorithms can catalyse the rapid analysis of health data, leading to precise diagnoses and timely interventions. Predictive models powered by AI can detect patterns and trends, aiding disease prevention and personalized treatment plans.

However, prioritizing privacy and security are essential. All AI/machine learning solutions must uphold stringent privacy standards, safeguarding patient data and confidentiality. When combined with privacy-enhancing technologies, integrating AI and machine learning in healthcare holds immense promise. Responsible use, coupled with privacy protection, can transform global health, enhance patient care and bridge healthcare gaps for a healthier, more equitable world.

Logan Kim, Chief Executive Officer, Nuvilab

AI is having a major impact on global health, where personalized data is becoming increasingly important for preventive medicine and precision health.

AI can be used to improve productivity and efficiency by automating tasks, such as diet recording. It can also innovate the user experience by providing personalized insights and solutions. For example, Nuvilabs AI technology can be used to analyse dietary habits and provide reports on the nutritional intake rate of each menu on personal mobile devices. Patients with chronic diseases, growing children and seniors in care facilities are especially in need of such a solution.

Diet recording in the healthcare industry is commonly operated by the 24-hour recall method, which is quite subjective and has a limited sample size. AI can be used to improve the accuracy and objectivity of diet recording, as well as lower costs. This will make AI a game changer in the field of nutrition and precision health.

AI technology is expected to bring about an innovation in diet recording, and personalized data accumulation will be possible beyond the limitations of the existing diet data. This will open up new insights and provide better outcomes in the global health landscape.

Andrs Lawson, Chief Executive Officer, Osana

In the face of complex and pressing global health problems, emerging technologies like AI and machine learning are transformative forces poised to make healthcare more accurate, accessible and economically sustainable.

AI and automation provide operating leverage for healthcare institutions, enhancing efficiency and improving outcomes. They can potentially transform healthcare delivery, increasing the supply and scalability of healthcare professionals. For instance, AI algorithms can analyse medical imaging data to identify early signs of diseases like cancer, often with greater accuracy than human doctors and at a lower cost. This allows for earlier, more effective treatment, potentially saving millions of lives.

However, it is essential to exercise forethought to guard against unintended consequences, which means adopting a safety-first, human-first approach in the development and deployment of these models. Technical challenges like privacy, bias and reliability must be intentionally addressed. Collaboration with key ecosystem stakeholders to certify models and develop governance frameworks for Responsible Healthcare General Intelligence is vital.

As we stand on the brink of this exciting new frontier, the vision of a healthier world, buoyed by AI and machine learning, is within our grasp. These technologies hold the promise of a transformative leap in our global health landscape, enabling us to counter medical challenges with unprecedented agility and accuracy. By harnessing AI and machine learning judiciously and responsibly, we can sculpt a future where quality healthcare is not a privilege for the few but a fundamental right for all.

Alicia Chong, Chief Executive Officer, Bloomer Health Tech

The convergence of continuous physiological data on lifestyle and environment is quickly leading to deep phenotyping. By combining this with the power of genomics, machine learning and AI will take healthcare to the next level.

At Bloomer Tech weve focused on understanding the cardiovascular system in women specifically, because even with over 30 years of evidence on sex differences, women continue to be harder to diagnose and treat, and consistently experience worse outcomes. Using AI to generate new digital biomarkers will transform this field and impact global health results, particularly for diseases and conditions that affect women disproportionately, differently and even uniquely.

Inspired by the technological transformation that resulted when we transitioned from the limitations of only being able to view photos through chemical processes and film, to enabling accessible, unlimited photos through compact, easy-to-use digital cameras, we are moving in the right direction.

We are pushing to move from existing, valuable though limited biomarkers that can only be viewed via chemical processes in labs, towards using AI trained with reliable data, continuously collected from everyday garments like women's bras.

The impact of ubiquitous access to data will be huge. Being able to read and examine the data when it's needed most instead of just starting a series of tests when it may already be too late will significantly impact peoples health across the world, allowing for proactive and preemptive care.

Daniella Gilboa, Chief Executive Officer, AIVF

IVF has revolutionized reproductive care, but it is highly dependent on expertise and experience. The most crucial dilemma in IVF is which embryo has the highest chances of becoming a healthy baby. Embryo evaluation done by experts is based on subjective human analysis.

Lets leap to the future and consider the alternative: a machine that generates new understanding of developmental milestones, recognizing features that cannot be seen by the human eye, incorporating data from different sources, providing an outcome thats more accurate than any human embryologist. A personalized treatment. This is the time for computational embryology, letting the machines do what we cannot and working together as a team. Alan Turing talked about machine vs. human. At AIVF we talk about a human-machine team. Lets team up with our AI models to do better medicine, to provide better care, to lower barriers of entry, and to allow everyone better access to the best care possible.

The application of precision medicine to save and improve lives relies on good-quality, easily-accessible data on everything from our DNA to lifestyle and environmental factors. The opposite to a one-size-fits-all healthcare system, it has vast, untapped potential to transform the treatment and prediction of rare diseasesand disease in general.

But there is no global governance framework for such data and no common data portal. This is a problem that contributes to the premature deaths of hundreds of millions of rare-disease patients worldwide.

The World Economic Forums Breaking Barriers to Health Data Governance initiative is focused on creating, testing and growing a framework to support effective and responsible access across borders to sensitive health data for the treatment and diagnosis of rare diseases.

The data will be shared via a federated data system: a decentralized approach that allows different institutions to access each others data without that data ever leaving the organization it originated from. This is done via an application programming interface and strikes a balance between simply pooling data (posing security concerns) and limiting access completely.

The project is a collaboration between entities in the UK (Genomics England), Australia (Australian Genomics Health Alliance), Canada (Genomics4RD), and the US (Intermountain Healthcare).

A year ago, a miracle happened that changed IVF history. An IVF clinic reported the birth of the first IVF baby following embryonic evaluation and selection by an AI model. Its not a dream anymore its here to stay and we should embrace it.

Alok Anil, Founder and CEO / Managing Director, Next Big Innovation Labs

The global health ecosystem is rapidly transitioning towards a personalized medicine-focused, outcome-based industry. Rapidly evolving biological threats like the recent COVID-19 pandemic highlight how a major overhaul is required in healthcare and pharmaceutical R&D. Emerging AI techniques can help process large data sets that pharma and healthcare industries have been capturing, and by building case-specific machine learning algorithms to streamline labour intensive processes, governments and companies save research dollars and time, while bringing efficiency to R&D processes.

MedTech devices such as 3D bioprinters with smart AI chips powering these machines to work round the clock and produce tissues on-demand could soon be the new normal towards bioprinting in tough environments like space. Pharmaceutical drug development cycles are becoming more efficient with the use of AI in early-stage drug development studies, moving towards fast-tracking to market critical lifesaving drugs that are under development.

The US Food and Drug Administration has announced its new modernization act 2.0, which enables the pharmaceutical industry to consider cell-based assays (like 3D bio-printed tissues) and computer models (like AI and machine learning-based approaches) to test for the safety and effectiveness of a drug a big push towards building stakeholder confidence in these emerging technologies.

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AI can make healthcare more accurate, accessible, and sustainable - World Economic Forum

AI that uses sketches to detect objects within an image could boost … – Science Daily

Teaching machine learning tools to detect specific objects in a specific image and discount others is a "game-changer" that could lead to advancements in cancer detection, according to leading researchers from the University of Surrey.

Surrey is set to present its unique sketch-based object detection tool at this year's Computer Vision, Pattern, and Recognition Conference (CVPR). The tool allows the user to sketch an object, which the AI will use as a basis to search within an image to find something that matches the sketch -- while discounting more general options.

Professor Yi-Zhe Song, leads this research at the University of Surrey's Institute for People-Centred AI. He commented:

"An artist's sketch is full of individual cues that words cannot convey concisely, reiterating the phrase 'a picture paints a thousand words'. For newer AI systems, simple descriptive words help to generate images, but none can express the individualism of the user or the exact match the user is looking for.

"This is where our sketch-based tool comes into play. AI is instructed by the artist via sketches to find an exact object and discount others. Which can be amazingly helpful in medicine, by finding more aggressive tumours, or helping to protect wildlife conservation by detecting rare animals."

An example that researchers use in their paper to the conference is of the tool helping to search a picture full of zebras -- with only a sketch of a single zebra eating to direct its search. The AI tool takes visual cues into account, such as pose and structure, but bases the decisions off the exact requirements given by the amateur artist.

Professor Song continued:

"The ability for AI to detect objects based on individual amateur sketches introduces a significant leap in harnessing human creativity in Computer Vision. It allows humans to interact with AI from a whole different perspective, no longer letting AI dictate the decisions, but asking it to behave exactly as instructed, keeping necessary human intervention."

This research will be presented at the Computer Vision, Pattern, and Recognition Conference (CVPR) 2023 which showcases world-leading AI research on a global stage. The University of Surrey sees an exceptional number of papers accepted to the CVPR 2023, far above other educational institutions, with over 18 papers accepted and one nominated for the Best Paper Award.

The University of Surrey is a research-intensive university, producing world-leading research and delivering innovation in teaching to transform lives and change the world for the better. The University of Surrey's Institute for People-Centred AI combines over 30 years of technical excellence in the field of machine learning with multi-disciplinary research to answer the technical, ethical and governance questions that will enable the future of AI to be truly people-centred. A focus on research that makes a difference to the world has contributed to Surrey being ranked 55th in the world in the Times Higher Education (THE) University Impact Rankings 2022, which assesses more than 1,400 universities' performance against the United Nations' Sustainable Development Goals (SDGs).

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AI that uses sketches to detect objects within an image could boost ... - Science Daily

Chamber Response to the UK Consultation on AI Regulation – uschamber.com

June 20, 2023

Response to the UK Consultation - AI regulation: a pro-innovation approach policy proposals

The U.S. Chamber of Commerce (Chamber) is the worlds largest business federation, representing the interests of more than three million enterprises of all sizes and sectors. The Chamber is a longtime advocate for strong commercial ties between the United States and the United Kingdom. Indeed, the Chamber established the U.S.-UK Business Council in 2016 to help U.S. firms navigate the challenges and opportunities from the UKs departure from the European Union. With over 40 U.S. and UK firms as active members, the U.S.-UK Business Council is the premier Washington-based advocacy organization dedicated to strengthening the commercial relationship between the U.S. and the UK.

U.S. and UK companies have together invested over $1.5 trillion in each others economies, directly creating over 2.75 million British and American jobs. We are each others strongest allies, single largest foreign investors, and the U.S. is the UKs largest trading partner.

The Chamber is also a leading business voice on digital economy policy, including on issues of data privacy, cross-border data flows, cybersecurity, digital trade, artificial intelligence, and e-commerce. In the U.S. and globally, we support sound policy frameworks that promote data protection, support economic growth, and foster innovation.

The Chamber welcomes the opportunity to provide His Majestys Government (HMG) with comments on its White Paper on implementing a pro-innovation approach to AI regulation. The Chamber commends the UK governments commitment to advancing a sound AI policy framework that supports economic growth, promotes consumer protection, and fosters innovation. We welcome further opportunities to discuss this input with colleagues from the Department for Science, Innovation and Technology, Office for Artificial Intelligence, and other UK government agencies, including British Embassy Washington as this strategy is implemented.

Additionally, we commend the Prime Minister's plan to host the inaugural Global Summit on AI Safety in the United Kingdom this year. We believe the Summit will serve as a platform to bring together key government representatives, academics, and leading technology companies to facilitate targeted and swift international action, focused on safety, security, and the vast opportunity at the forefront of AI technology.

AI is an innovative and transformational technology. The Chamber has long advocated for AI as a positive force, capable of addressing major societal challenges and spurring economic expansion for the benefit of consumers, businesses, and society. We promote rules based and competitive trade, and alignment around emerging technologies, including through standards promoting the responsible use of AI.

Our member companies already demonstrate the many examples of how AI technologies have positively impacted various industries. For instance, AI-powered predictive maintenance systems have revolutionized manufacturing by reducing downtime, optimizing equipment performance, and improving productivity, leading to tangible economic results. AI algorithms in healthcare have enhanced diagnostics accuracy, leading to faster and more accurate treatments that improve patient outcomes and save lives.

The Chamber has encouraged policymakers in multiple jurisdictions to refrain from instituting overly prescriptive regulations or regulations that do not account for the novel qualities of AI technologies. Potential negative examples include stifling innovation, e.g., if regulations are too restrictive or prescriptive, they may impede the development and deployment of new AI technologies. This can hinder the ability of businesses to explore novel use cases, create disruptive solutions, and drive technological advancements.

Overly prescriptive regulations can also reduce flexibility. AI technologies are rapidly evolving, and regulatory frameworks need to be adaptable to keep pace with these advancements. If regulations are rigid and fail to account for the dynamic nature of AI, they can limit the ability of businesses to adapt and iterate their AI systems as new technologies and methodologies emerge. Further, overly burdensome regulations can create a competitive disadvantage for the UK. For example, if regulations are inconsistent, fragmented, or overly burdensome in the UK compared to the EU, it could create a competitive disadvantage for businesses to operate in the UK. This can lead to a diversion of AI investments and talent to more favorable regulatory environments, impacting the competitiveness of the UK.

Aligned and globally recognized regulatory frameworks can help promote competition and foster global cooperation. Additionally, regulations that fail to consider the unique qualities of AI technologies may not effectively address the risks associated with AI systems. One-size-fits-all regulations might not adequately account for the diverse range of AI applications, their varying levels of risk, or the roles of different actors in the AI lifecycle. This can result in either overregulation that stifles low-risk applications or under regulation that fails to adequately mitigate risks in high-risk areas.

Excessive regulatory requirements can also impose substantial compliance costs on businesses, especially smaller enterprises that may lack the resources to navigate complex regulatory frameworks. If compliance becomes too burdensome in the UK, it could reduce the adoption of AI technologies, particularly for UK SMEs, hindering their ability to compete in the global market and reap the potential benefits of AI.

The better alternative is to develop targeted rules that can effectively address the tradeoffs associated with various AI use-cases and the roles of different actors in the AI developmental lifecycle. These rules should be proportionate and based on risk assessment, technologically impartial, and technically feasible. These approaches not only increase safety and build trust, but also allow for necessary flexibility and innovation, given that AI is a rapidly evolving technology. Controls to reduce the risk of AI harm should focus on areas such as unintended bias mitigation, model monitoring, fairness, and transparency. As the UK proceeds with establishing an AI governance regime, we ask that you keep in the mind the following broad principles:

Develop Risk-Based Approaches to Governing AI

Governments should incorporate risk-based approaches rather than prescriptive requirements into frameworks governing the development, deployment, and use of AI. It is simply not feasible to establish a uniform set of rules that can adequately address the distinctive features of each industry utilizing AI and its effect on individuals. Indeed, we recognize that AI use cases that involve a high risk should face a higher degree of scrutiny than a use case where the risk of concrete harm to individuals is low. New regulations should be risk-based and proportionate with a focus on high risk use cases rather than on entire sectors or technologies. Additionally, any risk assessment should account for the significant social, safety, and economic benefits that may accrue when an AI application replaces a human action.

It is crucial to remember that high risk sectors like autonomous vehicles and healthcare diagnostics for example, are already subject to extensive regulation by established bodies such as the UK Department for Transport (DfT) and Medicines and Healthcare Products Regulatory Agency (MHRA). While the integration of AI technologies within these sectors can introduce new dimensions of complexity and potential risks, it is again crucial to recognize that if AI-specific regulations are needed, they need to complement and align with already existing sector-specific regulations. As opposed to duplicating efforts or creating conflicting requirements which can increase risk.

Coordination between regulatory bodies is vital to ensuring that AI technologies are adequately governed to consider the unique challenges they present while avoiding unnecessary regulatory burdens. By leveraging the expertise and insights of established regulatory agencies like the DfT and MHRA, UK AI-specific regulations can build upon existing frameworks and address the novel aspects and risks associated with AI applications within highly regulated sectors.

Support Private and Public Investment in AI Research & Development (R&D)

Investment in R&D is essential to AI innovation. Governments should encourage and incentivize this investment by partnering with businesses at the forefront of AI, promoting flexible governance frameworks such as regulatory sandboxes, utilizing testbeds, and funding both basic R&D and that which spurs innovation in trustworthy AI. Policymakers should recognize that advancements in AI R&D happen within a global ecosystem where government, the private sector, universities, and other institutions collaborate across borders.

Abide by Internationally Recognized Standards

Industry-led, consensus-based standards are essential to digital innovation. Policymakers should support their development in recognized international standards bodies and consortia. Governments should also leverage industry-led standards, certification, and validation regimes on a voluntary basis whenever possible to facilitate the adoption of AI technologies. Global standards developed in collaboration with the business community that are voluntary, open, transparent, globally recognized, consensus-based, and technology-neutral are the best way to promote common approaches that are technically sound and aligned with policy objectives.

Embrace International Regulatory Cooperation

Regulators can advance multilateral cooperation on AI governance by strengthening mechanisms for global coordination on AI transparency. This includes promoting interoperable approaches to AI governance to enable best practices and minimize the risk of unnecessary regulatory divergences and trade restrictive practices emerging in the digital economy. Additionally, endorsing transparent, multi-stakeholder approaches to AI governance is essential, including in the development of voluntary standards, frameworks, and codes of practice that can bridge the gap between AI principles and its implementation. Multi-stakeholder initiatives have the greatest potential to identify gaps in AI outcomes and capabilities, and to mobilize AI actors to address them.

There are examples that the UK can turn to in this context. The approach being taken in the United States via the National Institute of Standards and Technology (NIST) and its Artificial Intelligence Risk Management Framework (AI RMF), as well as in Singapore and Japan, incorporate many of these characteristics. NIST and the AI RMF emphasize a risk-based approach to AI governance, recognizing the importance of proportionate regulations that account for different use cases and actors in the AI lifecycle. NIST's framework promotes safety, transparency, and accountability while fostering innovation, making it a suitable model for the UK's AI governance approach.

Singapore's Model AI Governance Framework and Japan's AI governance model offer valuable insights into effective AI governance practices. These frameworks also share common characteristics with the Chamber's proposed principles, such as stakeholder engagement, collaboration among government, industry, and academia, and the promotion of responsible and trustworthy AI. They demonstrate a commitment to balancing the benefits of AI innovation while ensuring safety and the well-being of individuals and society. The UK can draw inspiration from these models to develop a robust AI governance regime that aligns with international best practices and addresses the unique challenges posed by AI technologies.

To further enhance international regulatory cooperation, here are some measures HMG could consider in order to promote collaboration. This could be through the establishment of global frameworks that facilitate the harmonization of AI policies across borders. Governments could also consider creating platforms for information sharing and best practice exchange, enabling regulators to learn from one another's experiences and leverage collective knowledge. Additionally, joint research initiatives, for example between the U.S. and UK could foster collaboration among countries, academia, and industry to address common challenges and advance the understanding of AI's impacts. These collaborative efforts would promote consistent and effective regulation, prevent unnecessary regulatory divergences, and create a global ecosystem that encourages responsible AI development and deployment.

Accelerated Cooperation on AI

The Chamber and our members recognize that AI has the power to significantly transform societies and economies. To that end, we share a commitment to government action that unlocks the vast opportunities and addresses the potential risks arising from the rapid advancement of AI technologies. We emphasize the importance of engaging with companies, research institutions, civil society, and our allies and partners to ensure a well-rounded perspective. Our collective aim is to accelerate collaboration on AI, prioritizing the safe and responsible development of this technology.

Ethical Principles

In light of the increasing significance of ethical considerations in AI development and deployment, the Chamber believes it is imperative to address the importance of ethical principles in the context of AI governance. This should encompass essential aspects such as fairness, transparency, accountability, and the responsible use of AI. By incorporating these principles into regulatory frameworks, governments like the UK can promote public trust, minimize the potential for biases or discriminatory outcomes, and ensure that AI technologies are developed and deployed in a manner that aligns with societal values and norms. Emphasizing ethics in AI governance will help foster responsible innovation, mitigate risks, and ensure that the benefits of AI are distributed equitably across the UK population.

Non-Market Economies

Collaboration between the UK and U.S. on AI frameworks is paramount to counter the efforts of non-market economies, particularly China, to dominate the AI landscape. By aligning our approaches and sharing best practices, the UK and the U.S. can leverage each others expertise, innovation ecosystems, and regulatory frameworks to ensure a competitive and ethical AI environment. Strengthening transatlantic cooperation not only enhances the global influence of market-based economies, but also establishes a unified front in advocating for responsible AI governance that upholds democratic values, safeguards privacy and data protection, and promotes fair competition. Together, the UK and the U.S. can shape a global AI landscape that prioritizes innovation, transparency, and the well-being of individuals and societies, countering the influence of non-market economies and fostering an ecosystem that drives global AI advancement.

In conclusion, as the UK strives to be a policy leader in AI governance, it possesses a unique opportunity to inspire and encourage other nations to adopt these broad-based approaches. By championing risk-based frameworks, promoting private and public investment in AI research and development, embracing internationally recognized standards, fostering international regulatory cooperation, and accelerating collaboration on AI, the UK can set a powerful example for responsible and innovative AI governance. Through its leadership, particularly with the global AI summit in London this fall, the UK can help shape a global landscape that fosters trust, supports economic growth, and harnesses the transformative potential of AI for the betterment of societies worldwide.

Contact

Abel Torres

Executive Director, Center for Global Regulatory Cooperation

ATorres@uschamber.com

Zach Helzer

Senior Director, Europe & U.S.-UK Business Council

ZHelzer@uschamber.com

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Chamber Response to the UK Consultation on AI Regulation - uschamber.com