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In the 1970s, as researchers started to grasp the intricacies of genetics, they were inevitably faced with the ethical implications of intentionally altering genes in living organisms. While no technology existed at that time to make such modifications, it was clear that its emergence was just around the corner. In 1975, a landmark conference was held in Asilomar, California, bringing together not just scientists but also about 140 professionals ranging from legal experts to writers and journalists. The goal was to address the potential risks associated with gene manipulation. The conference led to the creation of a set of guiding principles that continue to have a lasting impact today. Asilomar serves as a singular example of effective self-regulation, proactive risk mitigation, and open communication with the public.

Today, as we stand on the cusp of a new, AI-driven, era, theres again a palpable sense of anticipation across the globe, while new risks and opportunities spread out before us. AI has swiftly transitioned from being a technological novelty to a pervasive force, reshaping our daily lives and industries, ranging from pioneering projects like OpenAI to autonomous transport. he allure of generative AI applications has dwarfed past technological frenzies. While innovations like the internet, steam engine, and printing press have previously ushered in transformative epochs, AI holds the promise of instigating the most monumental shift in human history.

However, as this wave of innovation surges forward, the need for a comprehensive regulatory framework becomes increasingly urgent. An important goal, agreed by several stakeholders, should be to ensure the ethical, secure, and equitable use of AI for all. The conversation is not a hypothetical debate about the distant future; its about what must be done today to secure a prosperous future for humanity and the planet.

Numerous stakeholdersgovernments, international organisations, NGOs, and tech giants, are scrambling to address the myriad challenges posed by AI. Whether driven by genuine concern or merely to cultivate a contemporary image, different initiatives are underway. The European Commission is pioneering efforts to craft the first-ever legal framework for AI[1]. The proposed legislation establishes different rules for different risk levels and has the potential to address AI risks for the society. Yet, it is uncertain whether this European effort can address all current and especially future challenges. Two glaring gaps persist in the European legislative effort but also in numerous parallel national or international initiatives.

First, the vast majority of the current efforts are focused on the present and the impacts of narrow AI, that is the current version of AI tools capable of performing specific tasks (like ChatGPT, AlphaFold or AlphaGo). Yet, this preoccupation with narrow AI obscures the monumental, potentially catastrophic challenges presented by Artificial General Intelligence (AGI). AGI represents a form of AI with the capacity to comprehend, learn, and apply knowledge across a wide range of tasks and domains[2]. An AGI system connected to the internet and myriad sensors and smart devices could solve complex problems, seek information by any means (even directly interacting with humans), make logical deductions, and even rewrite its own code. AGI does not exist today, yet according to estimations by experts[3] could be available between 2035-2040, a timeline that coincides with the typical time needed to solidify a global AGI treaty and governance system. This synchronicity underscores the pressing need to pivot our focus, infusing foresight methodologies to discern and tackle imminent challenges and prepare for unknown ones.

The second challenge for the ongoing legislative efforts is the fragmentation. AI systems, much like living organisms, transcend political borders. Attempting to regulate AI through national or regional efforts entails a strong potential for failure, given the likely proliferation capabilities of AI. Major corporations and emerging AI startups outside the EUs control will persist in creating new technologies, making it nearly impossible to prevent European residents from accessing these advancements. In this light, several stakeholders[4] suggest that any policy and regulatory framework for AI must be established on a global scale. Additionally, Europes pursuit of continent-wide regulation poses challenges to remaining competitive in the global AI arena, if the sector enjoys a more relaxed regulatory framework in other parts of the world. Furthermore, Article 6 of the proposed EU Artificial Intelligence Act introduces provisions for high-risk AI systems, requiring developers and deployers themselves to ensure safety and transparency. However, the provisions self-assessment nature raises concerns about its effectiveness.

What must be done

In this rapidly changing and complex global landscape, is there any political space for the EU to take action? The pan-European study OurFutures[5] reveals that the vast majority of participants express deep concern about the future, with technology-related issues ranking high on their list, alongside social justice, nature, well-being, education, and community. Moreover, despite the emerging signs of mistrust towards governments globally, citizens in the EU maintain confidence in government leaders as catalysts for positive change (picture 1), while they also prioritize human condition and environment over economic prosperity.

Picture 1: Who are the changemakers and what matters more (OurFutures)

The clock is ticking, but governments still have the opportunity to address societal concerns by taking bold steps. In the case of AI, the EU should assume a leadership role in global initiatives and embrace longtermism as a fundamental value, ensuring a sustainable future for current and future generations:

EU as a global sounding board. While the European Commissions legislative initiative on A.I. signifies a leap in the right direction, structured productive collaboration with key international partners like USA, China, UNESCO and OECD is essential, with the aim to set-up a global AI regulatory framework. The success of the Asilomar conference was rooted in its ability to create a voluntary set of globally respected rules. Violators faced condemnation from the global community, exemplified by the case of He Jiankui[6], who created the worlds first genetically edited babies and was subsequently sentenced to prison. Drawing from its tradition of negotiating regulations with many diverse stakeholders, the EU should champion a global initiative under the UN to forge a consensus on AI regulation, and adapt to the diversity of approaches shown by other AI actors.

A technology monitoring system. A global technology observatory has been already suggested by the Millennium Project[7], the Carnegie Council for Ethics in International Affairs[8] and other experts. This organization should be empowered to supervise AI research, evaluate high-risk AI systems, and grant ISO-like certifications to AI systems that comply with standards. It should track technological progress and employ foresight methods to anticipate future challenges, particularly as AGI looms on the horizon. Such an entity, perhaps aptly named the International Science and Technology Organization (ISTO), building on the work done by ISO/IEC and the IEEE on ad hoc standards, could eventually extend its purview beyond AI, encapsulating fields like synthetic biology and cognitive science. Avoiding the usual challengesdissent over nuances, apprehensions of national sovereignty, and the intricate dance of geopolitics, could be done through the emergence of such an organism from the mentioned already extant standardization organizations. However, the EU, with its rich legacy, is perfectly poised to champion this cause, in close collaboration with the UN to expedite its realization.

Embrace Longtermism. Longtermism, the ethical view that prioritizes positively influencing the long-term future, is a moral imperative in an era of exponential technological advancements and complex challenges like the climate crisis. Embracing longtermism means designing policies that address risks as we transition from sub-human AI to greater-than-human AI. For the European Commission, initiatives to address AI challenges should not be viewed as mere regulation but as a unique opportunity to etch its commitment to a secure, ethical AI future into history. A longtermism perspective in AI matches with the idea of AI Alignment put forth by numerous scholars[9], which addresses diverse concerns related to AI safety, aiming to ensure that AI remains aligned with our objectives and avoids unintended consequences of going astray.

As the world races against the clock to regulate AI, the EU has the potential to be a trailblazer. EUs initiatives to address AI challenges should not be considered merely as a regulatory endeavorits an unparalleled opportunity. Embracing longtermism and spearheading the establishment of an ISTO could be EUs crowning achievement. Its time for the EU to step up, engage in proactive diplomacy, and pave the way for a sustainable AI future that respects the values and concerns of people today and tomorrow.

[1] https://digital-strategy.ec.europa.eu/en/policies/regulatory-framework-ai

[2] https://www.gartner.com/en/information-technology/glossary/artificial-general-intelligence-agi

[3] Macey-Dare, Rupert, How Soon is Now? Predicting the Expected Arrival Date of AGI- Artificial General Intelligence (June 30, 2023). Available at SSRN:https://ssrn.com/abstract=4496418

[4] For example https://www.forbes.com/sites/hecparis/2022/09/09/regulating-artificial-intelligenceis-global-consensus-possible/?sh=a505f237035c

[5] https://knowledge4policy.ec.europa.eu/projects-activities/ourfutures-images-future-europe_en

[6] https://www.bbc.com/news/world-asia-china-50944461

[7] https://www.millennium-project.org/projects/workshops-on-future-of-worktechnology-2050-scenarios/

[8]Global AI Observatory (GAIO) : https://www.carnegiecouncil.org/media/article/a-framework-for-the-international-governance-of-ai

[9] For example: http://lcfi.ac.uk/projects/completed-projects/value-alignment-problem/

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What can the current EU AI approach do to overcome the challenges ... - Modern Diplomacy

There are so many new artificial intelligence products out there. Which ones are really worth your time?

If I had to pick one, it wouldnt be ChatGPT or Claude. It would be Perplexity.ai.

Since 1 October Ive logged more than 268 queries on Perplexity from my laptop alone (I use it on my phone, too). Its displacing a large number of my Google searches.

I decided to speak to the co-founder and CEO of Perplexity, Aravind Srinivas. Aravind and his team are hot off the heels of a $500 million funding round led by IVP.

You can watch our discussion in the video embedded in this post. The full hour-long discussion and transcript are open to paying members of Exponential View.

Of the many brilliant insights in our conversation, I was particularly excited to cover the following nine areas

Googles innovators dilemma.

The fuzzy art of shipping products built on AI models.

AI as ignition for a new era of human entrepreneurship.

Mapping out the route to AGI.

Going from from autocomplete to autopilot in the coming years.

Safety in a world with billions of AIs.

AI open-source: democratizing progress or losing control?

Beyond the technology: how do we get the public behind this journey?

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Azeem Azhar: Aravind, thanks for taking a few moments off the rocket ship to speak to me.

Link:
If I had to pick one AI tool... this would be it. - Exponential View

AI-generated image.

Predicting the weather is notoriously difficult. Not only are there a million and one parameters to consider but theres also a good degree of chaotic behavior in the atmosphere. But DeepMinds scientists (the same group that brought us AlphaGo and AlphaFold) have developed a system that can revolutionize weather forecasting. This advanced AI model leverages vast amounts of data to generate highly accurate predictions.

Weather forecasting, an indispensable tool in our daily lives, has undergone tremendous advancements over the years. Todays 6-day forecast is as good (if not better) than the 3-day forecast from 30 years ago. Storms and extreme weather events rarely catch people off-guard. You may not notice it because the improvement is gradual, but weather forecasting has progressed greatly.

This is more than just a convenience; its a lifesaver. Weather forecasts help people prepare for extreme events, saving lives and money. They are indispensable for farmers protecting their crops, and they significantly impact the global economy.

This is exactly where AI enters the room.

DeepMind scientists now claim theyve made a remarkable leap in weather forecasting with their GraphCast model. GraphCast is a sophisticated machine-learning algorithm that outperforms conventional weather forecasting around 90% of the time.

We believe this marks a turning point in weather forecasting, Googles researchers wrote in a study published Tuesday.

Crucially, GraphCast offers warnings much faster than standard models. For instance, in September, GraphCast accurately predicted that Hurricane Lee would make landfall in Nova Scotia nine days in advance. Currently used models predicted it only six days in advance.

The method that GraphCast uses is significantly different. Current forecasts typically use a lot of carefully defined physics equations. These are then transformed into algorithms and run on supercomputers, where models are simulated. As mentioned, scientists have this approach with great results so far.

However, this approach requires a lot of expertise and computation power. Machine learning offers a different approach. Instead of running equations on the current weather conditions, you look at the historical data. You see what type of conditions led to what type of weather. It gets even better: you can mix conventional methods with this new AI approach, and get accurate, fast readings.

Crucially, GraphCast and traditional approaches go hand-in-hand: we trained GraphCast on four decades of weather reanalysis data, from the ECMWFs ERA5 dataset. This trove is based on historical weather observations such as satellite images, radar, and weather stations using a traditional numerical weather prediction (NWP) to fill in the blanks where the observations are incomplete, to reconstruct a rich record of global historical weather, writes lead author Remi Lam, from DeepMind.

While GraphCasts training was computationally intensive, the resulting forecasting model is highly efficient. Making 10-day forecasts with GraphCast takes less than a minute on a single Google TPU v4 machine. For comparison, a 10-day forecast using a conventional approach can take hours of computation in a supercomputer with hundreds of machines.

The algorithm isnt perfect, it still lags behind conventional models in some regards (especially in precipitation forecasting). But considering how easy it is to use, its at least an excellent complement to existing forecasting tools. Theres another exciting bit about it: its open source. This means that companies and researchers can use and change it to better suit their needs.

Byopen-sourcing the model code for GraphCast,we are enabling scientists and forecasters around the world to benefit billions of people in their everyday lives. GraphCast is already being used by weather agencies, adds Lam.

The significance of this development cannot be overstated. As our planet faces increasingly unpredictable weather patterns due to climate change, the ability to accurately and quickly predict weather events becomes a critical tool in mitigating risks. The implications are far-reaching, from urban planning and disaster management to agriculture and air travel.

Moreover, the open-source nature of GraphCast democratizes access to cutting-edge forecasting technology. By making this powerful tool available to a wide range of users, from small-scale farmers in remote areas to large meteorological organizations, the potential for innovation and localized weather solutions increases exponentially.

No doubt, were witnessing another field where machine learning is making a difference. The marriage of AI and weather forecasting is not just a fleeting trend but a fundamental shift in how we understand and anticipate the whims of nature.

Read more here:
For the first time, AI produces better weather predictions -- and it's ... - ZME Science

On November 8, the Mineral County Sheriffs Office (MCSO), Mineral County School District (MCSD), and Mineral County District Attorneys Office sent out a joint press release responding to recent security events happening at the junior high and high schools.

Firearm ammunition was found in a classroom, causing the police to place the schools on a lockout as they searched lockers, students, and vehicles for any related contraband. During the search, the MCSO found two knives (one found in a car and another on a person) as well as multiple vape pens and a handgun. The handgun was in a car that was borrowed from a family member, and the adult owner of the vehicle was booked on a possession of a dangerous weapon on school property charge and released on a $1,140 bond.

The mother of that student said that her son didnt know the gun was in the car and its frustrating because the bullying problem is still out there. The focus is still on a kid that made an honest mistake, she says, while the bullying problem is still a big issue. She mentions that he has never gotten in trouble and is devastated at facing possible expulsion as well as damaging future job prospects.

Following the incidents, the MCSO, MCSD, and MC District Attorneys Office have implemented a zero-tolerance policy.

Effective immediately, all Sheriffs Office personnel responding to incidents of violence, weapons, or allegations of any violent or weapons-related activity at Mineral County schools, events, properties, or incidents involving juveniles will conduct proactive criminal investigations and pursue criminal charges to the fullest extent of the law, the joint statement reads. The Mineral County District Attorney will file criminal charges for any violent or weapons-related offenses and seek appropriate dispositions that educate, inform, but most importantly protect residents of Mineral County, and especially our youth, from violence, it further states.

Pursuant to NRS 202.265, a weapon on school property is a gross misdemeanor, subject to 364 days in jail, a fine of up to $2,000, or a combination of both, MC District Attorney T. Jaren Stanton later said.

The MCSO will now be conducting additional proactive patrols and walk-throughs before school, at lunchtime, and after school throughout the rest of the school year to enact the policy.

Prior to the November 8 lockout, Mineral County Sheriff Bill Ferguson says that over the years the school district, sheriffs office, and POOL/PACT (Nevada Public Agency Insurance Pool/Public Agency Compensation Trust) have developed plans for the safety of school students and staff in an event that a threat becomes present on campus(es).

We have a presence but unfortunately the whole nation is undermanned when it comes to law enforcement available, Sheriff Ferguson says.

The school lockout was prompted due to the police being called out to a stabbing incident between two juveniles at Lions Park a couple of nights before. A witness on scene told the police that one of the juveniles had a gun. It even goes back farther than that as three weeks ago, an altercation happened at a Hawthorne residence involving the same kids, which resulted with the mother of one of the kids chasing them down the street. One of those juveniles showed up to anothers workplace and threatened him, which led to the stabbing incident at Lions Park.

[The lockout] was the totality of circumstances that led us to where we were at, Ferguson added.

There has also been some talk about protecting students Fourth Amendment rights regarding unreasonable searches and seizures. The U.S. Fourth Amendment specifically reads: The right of the people to be secure in their persons, houses, papers, and effects, against unreasonable searches and seizures, shall not be violated, and no Warrants shall issue, but upon probable cause, supported by Oath or affirmation, and particularly describing the place to be searched, and the persons or things to be seized.

To this, Ferguson refers to the landmark case of New Jersey v. T.L.O. in which the US Supreme Court established a set of standards about public school officials being able to search students in a school environment without a warrant.

Sheriff Ferguson said that they are leaving it up to the school for how to reprimand the students who were caught with contraband considering they know them better, however, MCSD Superintendent Stephanie Kuehey could not be reached for comment at the time of publication.

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MCHS goes on lockout after weapons found on campus - Mineral County Independent-News

In November 2020, 45-year-old Elisabeth Rehn was preparing for a bath when five Seattle police officers broke down her door and streamed into her apartment. She barely had time to throw a coat over herself when she was stormed by the officers, who shouted commands and pointed their guns at her.

However, the officers had no reason to enter Rehn's apartment. According to a lawsuit filed last month, the police had gone to the wrong address. They weren't even in the correct building.

"Even after [police] knew or should have known that they had broken down the door of the wrong apartment, in the wrong building, the Defendants still continued to needlessly search her apartment while Ms. Rehn trembled in fear," the complaint states.

According to The Seattle Times, the officers believed they were responding to a "crisis call" about an intoxicated man who may have been attempting to push someone out of a window. While other first responders were able to reach the correct address, a second group of officers ended up in a different apartment building, where they mistakenly stormed Rehn's apartment.

Body camera footage shows the officers kicking Rehn's door in and rushing into her apartment with guns drawn. The officers are also captured searching through her apartment while Rehn sobs and trembles in fear.

The officers' "actions put Ms. Rehn in mortal fear that she was going to be assaulted or killed in this incident through no fault of her own," reads the complaint. "She was about to take a bath in her own apartment at the time, had disrobed in preparation for getting into her bath and barely had time to throw on a large coat to cover herself before the Defendant officers who entered her apartment shouted commands at her and trained one or more firearms on her."

Rehn's lawsuit argues that the officers' forced entry into her home violated her Fourth Amendment rights and subjected her to "substantial mental and emotional distress, fear for her physical well-being, invasion of privacy, loss of privacy, and other related damages."

This is far from the first time that police have mistakenly stormed into the wrong address. Cops frequently invade homes without properly checking they have the right address, leading to damaged property and terrified residents. Further, tragedy has occurred countless times when police officers have raided the wrong house and ultimately killed an innocent person living there.

While the exact scale of the problem is unclear, between 2017 and 2020, Chicago police alone raided at least 21 wrong addresses. And unfortunately, as is true with most instances of police violence, officers who kill or injure innocent homeowners when they invade the wrong address are usually protected by qualified immunity.

Continued here:
Cops Stormed Into a Seattle Woman's Home. It Was the Wrong ... - Reason