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This report provides an overview of standards published, under development and planned - and an assessment of their span for the purpose of identifying potential gaps.

EU Agency for Cybersecurity Executive Director, Juhan Lepassaar, declared: Advanced chatbot platforms powered by AI systems are currently used by consumers and businesses alike. The questions raised by AI come down to our capacity to assess its impact, to monitor and control it, with a view to making AI cyber secure and robust for its full potential to unfold. Using adequate standards will help ensure the protection of AI systems and of the data those systems need toprocess in order to operate. I trust this is the approach we need to take if we want to maximise the benefitsfor all of us to securely enjoy the services of AI systems to the full.

This report focuses on the cybersecurity aspects of AI, which are integral to the European legal framework regulating AI, proposed by the European Commission last year dubbed as the AI Act.

What is Artificial Intelligence?

The draft AI Act provides a definition of an AI system as software developed with one or more () techniques () for a given set of human-defined objectives, that generates outputs such as content, predictions, recommendations, or decisions influencing the environments they interact with. In a nutshell, these techniques mainly include: machine learning resorting to methods such as deep learning, logic, knowledge-based and statistical approaches.

It is indeed essential for the allocation of legal responsibilities under a future AI framework to agree on what falls into the definition of an 'AI system'.

However, the exact scope of an AI system is constantly evolving both in the legislative debate on the draft AI Act, as well in the scientific and standardisation communities.

Although broad in contents, this report focuses on machine learning (ML) due to its extensive use across AI deployments. ML has come under scrutiny with respect to vulnerabilities particularly impacting the cybersecurity of an AI implementation.

AI cybersecurity standards: whats the state of play?

As standards help mitigate risks, this study unveils existing general-purpose standards that are readily available for information security and quality management in the context of AI. In order to mitigate some of the cybersecurity risks affecting AI systems, further guidance could be developed to help the user community benefit from the existing standards on AI.

This suggestion has been based on the observation concerning the software layer of AI. It follows that what is applicable to software could be applicable to AI. However, it does not mean the work ends here. Other aspects still need to be considered, such as:

Further observations concern the extent to which the assessment of compliance with security requirements can be based on AI-specific horizontal standards; furthermore, the extent to which this assessment can be based on vertical/sector specific standards calls for attention.

Key recommendations include:

Regulating AI: what is needed?

As for many other pieces of EU legislation, compliance with the draft AI Act will be supported by standards. When it comes to compliance with the cybersecurity requirements set by the draft AI Act, additional aspects have been identified. For example, standards for conformity assessment, in particular related to tools and competences, may need to be further developed. Also, the interplay across different legislative initiatives needs to be further reflected in standardisation activities an example of this is the proposal for a regulation on horizontal cybersecurity requirements for products with digital elements, referred to as the Cyber Resilience Act.

Building on the report and other desk research as well as input received from experts, ENISA is currently examining the need for and the feasibility of an EU cybersecurity certification scheme on AI. ENISA is therefore engaging with a broad range of stakeholders including industry, ESOs and Member States, for the purpose of collecting data on AI cybersecurity requirements, data security in relation to AI, AI risk management and conformity assessment.

AI and cybersecurity will be discussed in two dedicated panels:

ENISA advocated the importance of standardisation in cybersecurity today, at the RSA Conference in San Francisco in the Standards on the Horizon: What Matters Most? in a panel comprising the National Institute of Standards and Technology (NIST).

Further information

Cybersecurity of AI and standardisation 2023 ENISA report

Securing Machine Learning Algorithms 2021 ENISA report

The proposal AI Act

The proposal Cyber Resilience Act

Contact

For press questions and interviews, please contactpress (at) enisa.europa.eu

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Mind the Gap in Standardisation of Cybersecurity for Artificial ... - ENISA

Tuesday 02 May 2023 5:15 am

The future is AI and if London wants to be a global leader, we need to strike the right balance of innovation and regulation here in the City, writes Chris Hayward

A cornerstone of Londons success in recent years has been the focus on digitalisation and innovation. These twin pillars have helped build the City into one of the worlds most advanced markets.

Indeed, recent competitiveness benchmarking report from the City of London Corporation showed that despite geopolitical shifts, a challenging global macroeconomic environment, and difficult financial market conditions, London remains a world leading financial centre.

But that competitive advantage is under threat like never before. Recent research by SCM Direct suggested that Britains top 100 companies would be worth towards 500bn more if they moved their stock market listings to New York.

The UK has a dynamic venture capital sector, but we must do a better job of incentivising capital into our innovative start-ups so that they list in London, rather than elsewhere.

We mustnt dig our heads in the sand and ignore this threat. We need to accept that we need to do better, be more attractive, more innovative, if we are to excel in the future.

The Future Growth Fund, targeting up to 50bn of private sector defined contribution pension schemes, would inject transformational capital into industries such as fintech, biotech, life sciences, and green technology.

Finding new sources of capital so that British companies can both start-up and scale-up without leaving our shores, is just one of several issues.

The future of our economy is digital. We must therefore ensure that we have the right regulatory environment, one that does not stifle innovation. Regulation can help technology grow. To paraphrase Goldilocks, regulation must be not too hot and not too cold, but just right.

Conversations led by the Financial Conduct Authority on reviewing corporate governance structures and replacing the current rules with a single listing category with one set of requirements are positive steps forward.

I have no doubt that by focusing on innovation we can find a path to prosperity once again.

One of the areas we need to show leadership is in artificial intelligence. At a time when everyone, everywhere, is looking to stimulate economic growth, PwC has predicted that UK GDP will be 10.3 per cent higher in 2030 because of AI. Thats the equivalent of an additional 232bn greater than the annual cost of the NHS in England making it one of the biggest economic opportunities in a generation.

The second is digital cross border payments. New technologies are revolutionising financial services. As we explore this new frontier with UK pilots currently taking place it will be vital that we follow a path that allows innovative technologies to thrive and protects consumers through agile and proportionate regulation.

The third is cyber security. Last year, UK cyber revenues hit over 10bn. This growing industry supports almost 2,000 businesses, employing nearly 60,000 people. As the world becomes more geopolitically unstable, cyber security will only grow. It is vital that we in the UK ride this developing wave of success so that our critical national infrastructure can endure any storms that come.

By striking the right balance of innovation and regulation, the City has a real opportunity to become the worlds leading tech capital.

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Artificial intelligence could save London from losing our competitive edge to the US - City A.M.

International Business Machines Chief Executive Officer Arvind Krishna said the company expects to pause hiring for roles it thinks could be replaced with artificial intelligence in the coming years.

Hiring in back-office functions such as human resources will be suspended or slowed, Krishna said in an interview. These non-customer-facing roles amount to roughly 26,000 workers, Krishna said. I could easily see 30% of that getting replaced by AI and automation over a five-year period.

That would mean roughly 7,800 jobs lost. Part of any reduction would include not replacing roles vacated by attrition, an IBM spokesperson said.

As artificial intelligence tools have captured the public imagination for their ability to automate customer service, write text and generate code, many observers have worried about their potential todisrupt the labor market. Krishnas plan marks one of the largest workforce strategies announced in response to the rapidly advancing technology.

More mundane tasks such as providing employment verification letters or moving employees between departments will likely be fully automated, Krishna said. Some HR functions, such as evaluating workforce composition and productivity, probably wont be replaced over the next decade, he added.

IBM currently employs about 260,000 workers and continues to hire for software development and customer-facing roles. Finding talent is easier today than a year ago, Krishna said. The company announcedjob cutsearlier this year, which may amount to about 5,000 workers once completed. Still, Krishna said IBM has added to its workforce overall, bringing on about 7,000 people in the first quarter.

Krishna, who has been CEO since 2020, has worked to focus the century-old company around software and services such as hybrid cloud. He has divested lower-growth businesses like managed infrastructure unit Kyndryl Inc. and part of the Watson Health business. The company is currently consideringselling its weather unit.

Armonk, New York-based IBMtopped profit estimatesin its most recent quarter due to expense management, including the earlier-announced job cuts. New productivity and efficiency steps are expected to drive $2 billion a year in savings by the end of 2024, Chief Financial Officer James Kavanaugh said on the day of earnings.

Until late 2022, Krishna said he believed the US could avoid a recession. Now, he sees the potential for a shallow and short recession toward the end of this year. Though the companys strong software portfolio, including acquired unit Red Hat, should help it maintain steady growth despite worsening macroeconomic concerns, wrote Bloomberg Intelligences Anurag Rana last week.

Continued here:
IBMs CEO expects A.I. to be so good at back office work that he plans to pause hiring humans for those jobs - Fortune

Artificial intelligence (AI)

Conservationists in the Brazilian Amazon are using a new tool to predict the next sites of deforestation and it may prove a gamechanger in the war on logging

Jill Langlois

Sat 29 Apr 2023 11.00 EDT

It took just the month of March this year to fell an area of forest in Triunfo do Xingu equivalent to 700 football pitches. At more than 16,000 sq km, this Environmental Protection Area (APA) in the south-eastern corner of the Brazilian Amazon, in the state of Par, is one of the largest conservation areas in the world. And according to a new tool that predicts where deforestation will happen next, its also the APA at highest risk of even more destruction.

The tool, PrevisIA, is an artificial intelligence platform created by researchers at environmental nonprofit Imazon. Instead of trying to repair damage done by deforestation after the fact, they wanted to find a way to prevent it from happening at all.

PrevisIA pinpointed Triunfo do Xingu as the APA at highest risk of deforestation in 2023, with 271.52 sq km of forest in the conservation area expected to be lost by the end of the year. About 5 sq km had already been destroyed in March.

Home to the endangered white-cheeked spider monkey and other vulnerable and near-threatened species, such as the hyacinth macaw and the jaguar, the conservation area is rich in biodiversity often found nowhere else in the world. But its land runs through two municipalities, Altamira and So Flix do Xingu, with some of the highest rates of deforestation in the country. And despite Triunfo do Xingu being protected under Brazilian law, illegal activities mining, logging, land-grabbing have ravaged the area, stripping it bare in places.

But with PrevisIA, there is the potential for change. Imazon is now establishing partnerships with authorities across the region, with the aim of stopping deforestation before it starts.

Destruction across the Brazilian Amazon is creeping close to an all-time high. According to SAD, Imazons Deforestation Alert System, deforestation this March tripled compared to the same month last year, and the first quarter of 2023 saw 867 sq km of rainforest destroyed the second largest area felled in the past 16 years.

The idea for PrevisIA emerged in 2016, when the team at Imazon analysed data collected from SAD satellite images. Tired of getting notifications after large swaths of forest had already been cleared, they asked themselves: is it possible to generate short-term deforestation prediction models?

Existing deforestation prediction models were long-term, looking at what would happen in decades, says Carlos Souza Jr, senior researcher at Imazon and project coordinator of PrevisIA and SAD. We needed a new tool that could get ahead of the devastation.

Souza and his team a computer engineer, a consultant in geostatistics and two researchers began developing a new model capable of generating annual predictions. They published their findings in the journal Spatial Statistics in August 2017.

The model takes a two-pronged approach. First, it focuses on trends present in the region, looking at geostatistics and historical data from Prodes, the annual government monitoring system for deforestation in the Amazon. Understanding what has happened can help make predictions more precise. When already deforested areas are recent, this indicates gangs are operating in the area, so theres a higher risk that nearby forest will soon be wiped out.

Second, it looks at variables that put the brakes on deforestation land protected by Indigenous and quilombola (descendent of rebel slaves) communities, and areas with bodies of water, or other terrain that doesnt lend itself to agricultural expansion, for instance and variables that make deforestation more likely, including higher population density, the presence of settlements and rural properties, and higher density of road infrastructure, both legal and illegal.

They are the arteries of destruction of the forest, says Souza, referring to unofficial roads that snake through the Amazon to facilitate illegal industrial activities. These roads create the conditions for new deforestation.

Monitoring the construction of these roads is crucial to predicting and eventually preventing deforestation. According to Imazon, 90% of accumulated deforestation is concentrated within 5.5km of a road. Logging is even closer, with 90% taking place within 3km, and 85% of fires within 5km.

Researchers used to comb through thousands of satellite images to see whether they could spot new roads slicing through the biome. With PrevisIA, the work is handed over to an AI algorithm that automates mapping, allowing for quicker analysis and, in turn, more frequent updates.

But without a robust computational platform and the ability to update road maps more quickly, PrevisIA couldnt be put into action. It wasnt until 2021 that the team at Imazon partnered with Microsoft and Fundo Vale, acquiring the cloud computing power they needed to run the AI algorithm for mapping roads.

Technology has always been the reason weve been able to control deforestation, says Juliano Assuno, executive director of the Climate Policy Initiative and professor at the Pontifical Catholic University of Rio de Janeiro (PUC-Rio). PrevisIA is a natural evolution of this incorporation of technology in the fight to protect the Amazon, and one with a lot of potential.

While technology is crucial for PrevisIA to work, who uses it will be what makes the difference. Assuno notes the obvious entities who could benefit from using PrevisIA government agencies at all levels, tasked with protecting the rainforest but he also cites those not directly involved in monitoring the Amazon, banks, investors and those who buy products from the region, who could use the information to make better decisions, both from an economic and an environmental point of view.

So far, Imazon has official partnerships with a handful of state prosecutors offices in the region. They hope that their use of PrevisIA will lead to less punishment and more prevention.

We dont want to have to keep coming in after the damage has already been done, says Jos Godofredo Pires dos Santos, a public prosecutor in Par and coordinator of the environmental operational support centre. Were always working to penalise these environmental crimes and irregularities. But from the environmental side, the damage has already been done. We want to reverse that logic. We want to find a way to prevent it from ever happening.

Pires dos Santoss team has been having weekly meetings with Imazon to get up to speed on how they can best use PrevisIA. He expects theyll start putting the system to use in the second half of 2023.

In Acre in western Brazil, the state prosecutors office hopes for the same. The idea, says prosecutor Arthur Cezar Pinheiro Leite, is for PrevisIA to notify monitoring agencies of high-risk areas, so they can keep a closer watch and so that prosecutors can warn property owners or others in the region that they will be held responsible if deforestation occurs.

We want them to know were aware of whats going on, Leite says. And if that deforestation does still manage to happen, theyll be punished and serve as an example for others considering doing the same.

So far, Souza says PrevisIAs accuracy has been fantastic. Of all its deforestation alerts, 85% have been within 4km of the predicted location. Just over 49% of alerts have been in areas classified as high or very high risk. He and his team are constantly working to improve their model, but he also hopes that, one day, they get it wrong.

If that happens, he says, itll mean prevention is working.

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Could AI save the Amazon rainforest? - The Guardian

Jobs Most Impacted by ChatGPT and Similar AI Models

On November 30, 2022, OpenAI heralded a new era of artificial intelligence (AI) by introducing ChatGPT to the world.

The AI chatbot stunned users with its human-like and thorough responses. ChatGPT could comprehend and answer a variety of different questions, make suggestions, research and write essays and briefs, and even tell jokes (amongst other tasks).

Many of these skills are used by workers in their jobs across the world, which begs the question: which jobs will be transformed, or even replaced, by generative AI in the coming future?

This infographic from Harrison Schell visualizes the March 2023 findings of OpenAI on the potential labor market impact of large language models (LLMs) and various applications of generative AI, including ChatGPT.

The OpenAI working paper specifically examined the U.S. industries and jobs most exposed to large language models like GPT, which the chatbot ChatGPT operates on.

Key to the paper is the definition of what exposed actually means:

A proxy for potential economic impact without distinguishing between labor-augmenting or labor-displacing effects. OpenAI

Thus, the results include both jobs where humans could possibly use AI to optimize their work, along with jobs that could potentially be automated altogether.

OpenAI found that 80% of the American workforce belonged to an occupation where at least 10% of their tasks can be done (or aided) by AI. One-fifth of the workforce belonged to an occupation where 50% of work tasks would be impacted by artificial intelligence.

Here is a list of jobs highlighted in the paper as likely to see (or already seeing) AI disruption, where AI can reduce the time to do tasks associated with the occupation by at least 50%.

Analysis was provided by a variety of human-made models as well as ChatGPT-4 models, with results from both showing below:

Editors note: The paper only highlights some jobs impacted. One AI model found a list of 84 additional jobs that were fully exposed, but not all were listed. One human model found 15 additional fully exposed jobs that were not listed.

Generally, jobs that require repetitive tasks, some level of data analysis, and routine decision-making were found to face the highest risk of exposure.

Perhaps unsurprisingly, information processing industries that involve writing, calculating, and high-level analysis have a higher exposure to LLM-based artificial intelligence. However, science and critical-thinking jobs within those industries negatively correlate with AI exposure.

On the flipside, not every job is likely to be affected. Heres a list of jobs that are likely least exposed to large language model AI disruption.

Naturally, hands-on industries like manufacturing, mining, and agriculture were more protected, but still include information processing roles at risk.

Likewise, the in-person service industry is also expected to see minimal impact from these kinds of AI models. But, patterns are beginning to emerge for job-seekers and industries that may have to contend with artificial intelligence soon.

OpenAI analyzed correlations between AI exposure in the labor market against a jobs requisite education level, wages, and job-training.

The paper found that jobs with higher wages have a higher exposure to LLM-based AI (though there were numerous low-wage jobs with high exposure as well).

Professionals with higher education degrees also appeared to be more greatly exposed to AI impact, compared to those without.

However, occupations with a greater level of on-the-job training had the least amount of work tasks exposed, compared to those jobs with little-to-no training.

The potential impact of ChatGPT and similar AI-driven models on individual job titles depends on several factors, including the nature of the job, the level of automation that is possible, and the exact tasks required.

However, while certain repetitive and predictable tasks can be automated, others that require intangibles like creative input, understanding cultural nuance, reading social cues, or executing good judgement cannot be fully hands-off yet.

And keep in mind that AI exposure isnt limited to job replacement. Job transformation, with workers utilizing the AI to speed up or improve tasks output, is extremely likely in many of these scenarios. Already, there are employment ads for AI Whisperers who can effectively optimize automated responses from generalist AI.

As the AI arms race moves forward at a rapid pace rarely seen before in the history of technology, it likely wont take long for us to see the full impact of ChatGPT and other LLMs on both jobs and the economy.

This article was published as a part of Visual Capitalist's Creator Program, which features data-driven visuals from some of our favorite Creators around the world.

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Which Jobs Will Be Most Impacted by ChatGPT? - Visual Capitalist