created a safe corridor for Ukraine’s grain exports from three Ukrainian ports – Odesa, Yuzhny and Chornomorsk.

metacognitive prompts.

hile AI has the potential to help students learn

In this scenario, the AI aids with personalized, readily available tutoring and coaching outside of the classroom and the classroom transforms into ahub of systematic engagement

Such changes foster an active learning environment, inviting each student to engage with class concepts, articulate reasoning, and actively construct knowledge

AI as Simulators: Build Your Own

AI as Simulator: Creating Opportunities for Practice

applying that concept actively in a novel situation requires a level of automation –students have to “think on their feet” as they apply what they know in a new way

Your assessment should focus on how well the AI has explained and illustrated the concept, not on the quality of its creative output; consider how the AI has applied the concept and not whether the poem or dialogue is engaging or unique.

Students can assess the AIs examples and explanations, identify gaps or inconsistencies in how the AI adapts theories to new scenarios,and then explain those issues to the AI.The student’s assessment of the AI’s output and their suggestions for improvement of that output is a learning opportunity.

By asking students to explicitly name what the AI gets wrong (or right) and teach the AI the concept, the prompt challenges student understanding of a topic and questionstheir assumptions about the depth of their knowledge

This is because teaching involves “elaborative interrogation” or explaining a fact or topic in detail and this requires a deep processing of the material and invokes comparison mechanisms: to generate an explanation, students much compare concepts and consider differences and similarities between concepts.

Teaching others helps students learn

AI as Coach: Reflection Prompt

Metacognition plays a pivotal role in learning, enabling students to digest, retain, and apply newfound knowledge.

This type of metacognition involves“reflection after action”

Metacognitive exercises can help students generalize and extract meaning from an experience or simulate future scenarios.

AI Tutor: Instructions for students

students get more opportunities to restate ideasin their own words, explain, think out loud, answer questions, and elaborate on responses than they would in a classroom, where time is limited and one-on-one instruction isn’t possible

Tutoring is inherently interactive and can involve a number of learning strategies including:questioning(by both the tutor and the student); personalized explanations and feedback(the tutor can correct misunderstandings in real-time and provide targeted advice based on the student's unique needs); collaborative problem-solving(tutors may work through problems together with students, and not justshow them the solution); and real-time adjustment(based on the student's responses and progress, a tutor mayadjust the pace, difficulty level, making the learning process dynamic and responsive)

Tutoring,particularly high-dosage tutoring,has been shown to improve learning outcomes

n a paragraph,briefly discuss what you learned from using the tool. How well did it work? Did anything surprise you? What are some of your takeaways in working with the AI? What did you learn about your own work? What advice or suggestions did it give you? Was the advice helpful?

hat reflection can also serve as a springboard for a class discussion that serves a dual purpose: a discussion about the topic or concept and about how to work with the AI

Getting feedback on their work from the AI is an opportunity to practiceand improve,but that feedback should be considered critically, and students should be asked to articulate how and why the feedback they received is effective (or not).

Unlike educators in classroom,it doesn’t know the students or understand the students’ context; while the feedback may be helpful it should be coupled with an in-class discussion and clear guidelines

s one possible form of feedback

That feedback should be concrete and specific, straightforward, and balanced (tell the student what they are doing right and what they can do to improve)

an also give you a sense of where students are in their learning journey

Students should report out their interactions with the AI and write a reflection about the guidance and help the AI provided and how they plan to incorporate (or not) the AI’s feedback to help improve their work.

While ongoing, tailored feedback is important, it is difficultand time-consuming to implement in a large class setting. The time and effort required to consistently provide personalized feedback to numerous students can be daunting.

When feedback is coupled with practice itcreates anenvironment that helps students learn

Researchers notethe significance of incorporating feedback intothe broader learning process, as opposed to providing it at the conclusion of a project, test, or assignment.

Effective feedback pinpoints gaps and errors, and offers explanations about what students should do to improve

Making mistakes can help students learn. particularly if those mistakes are followed by feedback tailored to the individual student

Large Language Models are prone to producing incorrect, but plausible facts, a phenomenon known as confabulation or hallucination.

Prompts are simply the text given to the LLM in order to produce an output.

Our guidelines challenge students to remain the “human in the loop” and maintain that not only are students responsible for their own work but they should actively oversee the AIs output, check with reliable sources, and complement any AI output with their unique perspectives and insights. Our aim is to encourage students to critically assess and interrogate AI outputs, rather than passively accept them.

increasing metacognition

: to help students learn with AI and to helpthem learn about AI

how and when to use AI as they instill best practices in AI-assisted learning.

hese tools offer the potential for adaptivelearning experiences tailored to individual students’needs and abilities, as well as opportunities to increase learning through a variety of other pedagogical methods.

This paper examines the transformative role of Large Language Models (LLMs) in education and their potential as learning tools, despite their inherent risks and limitations. The authors propose seven approaches for utilizing AI in classrooms: AI-tutor, AI-coach, AI-mentor, AI-teammate, AI-tool, AI-simulator, and AI-student, each with distinct pedagogical benefits and risks. The aim is to help students learn with and about AI, with practical strategies designed to mitigate risks such as complacency about the AI’s output, errors, and biases. These strategies promote active oversight, critical assessment of AI outputs, and complementation of AI's capabilities with the students' unique insights. By challenging students to remain the "human in the loop", the authors aim to enhance learning outcomes while ensuring that AI serves as a supportive tool rather than a replacement. The proposed framework offers a guide for educators navigating the integration ofAI-assisted learning in classrooms.

A company that doesn’t like the rules could threaten to pack up and leave. Then what? 

“Keeping the details of AI technologies secret is likely to thwart good-faith researchers trying to protect the public interest, as well as competition, and open science,”

agreed not to share: the parameters that are known as the “weights” of their algorithms.

a detailed metadata trail that reflects the history of a given image.

It is also not clear who those experts will be, how they will be chosen, whether the same experts will be tasked with examining all the systems, and by what measure they will determine risk.

he outlined a plan to bring lawmakers up to speed on emerging technology by convening at least nine panels of experts to give them a crash course in A.I. and help them craft informed legislation.

foundation model providers generally do not comply with draft requirements to describe the use of copyrighted training data, the hardware used and emissions produced in training, and how they evaluate and test models.

I support an Anti-AI movement in the sense that we should have some opposition questioning what's going on.

national unification programme for 2030

Bargaining is possible in relation to issues linked to tactical time – or even strategic time; but never on issues that belong to historical time.

by rejecting Christianity, we have in fact become hedonistic pagans.

thought that the rejection of religion and Christianity would be followed by the emergence of an ideal, enlightened community based on an understanding of the good and the common good, living a free and superior life according to recognised, sociologically based societal truths.

with spiritual foundations in mind, and digging a shovelful deeper, it is also worth saying that at the base of the Hungarian Constitution and the intellectual foundations of the new era there lies an anthropological insight

If you read the constitutions of other European countries, which are liberal constitutions, you will see that at the heart of them is the “I”. If you read the Hungarian Constitution, you will see that it is centred on the “we”.

the federalists are carrying out an attempt to oust us; they have openly said that they wanted a change of government in Hungary.

These could only be introduced in the European Union because the British left and we V4 members could not prevent them – and indeed the V4 was attacked by the federalists. We can all see the result.

I am not even going to talk about clever little European tricks such as the sudden doubling – in a single year – of the volume of goods exported from Germany to Kazakhstan.

either to decouple, or to participate in international competition. As they say in Brussels, “de-risking or connectivity”.

The amount paid for the European Union’s imports of gas and oil – the two together – was 300 billion euros before the Russian war, and 653 billion euros last year.

They call this seclusion “decoupling” – or, more subtly, “de-risking”, which is a form of risk reduction.

by the size of their economies, by their national GDPs, we see that in the rankings for 2030 Britain, Italy and France will have dropped out of the top ten where they still are today; and Germany – now fourth – will have slid down to tenth place.

“native genocide”, which I think means the extermination of indigenous peoples; slavery and the slave trade; and “reparatory justice”, meaning reparations for injustices.

The EU has about 400 million people; and if I add in the rest of the Western world, that is another 400 million. So this amounts to 800 million people, surrounded by another seven billion. And the European Union has an accurate view of itself: it is a rich union, but a weak one.

the settling of the new equilibrium will not happen overnight – or even from one month to the next

the “Thucydides Trap”,

Experience shows that the dominant great power tends to see itself as more benevolent and better-intentioned than it really is, and attributes malice to its challenger more often than is – or should be – justified

The bad news is that of the sixteen instances thus identified, twelve have ended in war, and only four were peacefully resolved

And it can neutralise the chief US weapon, the chief US weapon of power, which we call “universal values”

“Ending the century of humiliation” – or, to paraphrase the Americans, “Make China Great Again”.

So China has quite simply created its own: we see the BRICS and the One Belt One Road Initiative; and we also see the Asian Infrastructure Investment Bank, the development resources of which are several times greater than the development resources of all the Western countries. 

there are no eternal winners and no eternal losers

In 2010 the US and the European Union contributed 22 – 23 per cent of total world production; today the US contributes 25 per cent and the European Union 17 per cent. In other words, the US has successfully repelled the European Union’s attempt to move up alongside it – or even ahead of it.

we also had a plan, which we expressed as the need to create a great free trade zone stretching from Lisbon to Vladivostok.

after its own civil war, from the 1870s onwards the United States grew to be the preeminent country, and its inalienable right to world economic supremacy is part of its national identity, and a kind of article of faith.

What has happened is that China has made the roughly three-hundred-year journey from the Western industrial revolution to the global information revolution in just thirty years.

But it has turned out that in fact this issue, the liberation of China, belongs to the historical timeframe; because as a result of that liberation, the United States – and all of us – are now facing a greater force than the one we wanted to defeat. 

Back then the US decided to free China from its isolation, obviously to make it easier to deal with the Russians; and so it put that issue in the strategic timeframe.

tactical time, strategic time, and historical time.

you have to simultaneously visualise three timeframes

then today “Western values” mean three things: migration, LGBTQ, and war.

because the Ministry of Foreign Affairs of Romania – which I understand to belong more to the presidential branch of power – has come to my aid and sent me a démarche.

Some key takeaways include :

"They" being the multiple competing entities working in the field right now, most of whom are trying to make the barrier to entry in this field millions of dollars higher than it otherwise would be through mandatory paid consultations with "Safety experts" that could hypothetically double as corporate espionage assets to steal your secrets before you publish them.

This form of analysis is antithetical to Wittgenstein's approach, particularly in his later work, where he stressed the importance of seeing things as interconnected wholes rather than reducing them to their constituent parts.

Wittgenstein introduced the idea of "language games," arguing that the meaning of words is determined by their usage in specific forms of life, or social practices. This stands somewhat in opposition to the detailed, precise and generalized logical framework outlined in the provided ontology, which assigns fixed roles and properties to human brains, AI models, and animal consciousness across all contexts.

There are a couple of reasons for this, and they predominantly center around Wittgenstein's ideas of language games, private language arguments, and his opposition to reductionism.

Heidegger's Dasein refers to the unique manner in which humans exist, embodying a subjective, in-the-world mode of being.

This restriction will stop these people from proliferating and creating fully open source LLMs based on Llama 2 outputs. So, say goodbye to improvements in some of the open source models.

ovators and th

significant model public releases within scope

introduced after the watermarking system is developed

reat unreleased AI model weights for models in scope as core intellectual property for their business,

establishor joina forum or mechanism through which they can develop, advance, and adopt shared standards and best practices for frontier AI safety,

Companies commit to advancing this area of research, and to developing a multi-faceted, specialized, and detailed red-teaming regime, including drawing on independent domain experts, for all major public releases of new models within scope

Where commitments mention particular models, they apply only to generative models that are overall more powerful than the current industry frontier (

hese voluntary commitmentsto remain in effect until regulations covering substantially the same issues come into force

designed to advancea generative AI legal and policy regime

Realizing the promise and minimizing the risk of AI will require new laws, rules, oversight, and enforcement.

only a first step in developing and enforcing binding obligations to ensure safety, security, and trus

the Administration will work with allies and partners to establish a strong international framework to govern the development and use of AI.

robust technical mechanisms to ensure that users know when content is AI generated

will be carried out in part by independent experts

immediately

the G-7 Hiroshima Process—as a critical forum for developing shared principles for the governance of AI—as well as the United Kingdom’s leadership in hosting a Summit on AI Safety, and India’s leadership as Chair of the Global Partnership on AI. 

It has already consulted on the voluntary commitments with Australia, Brazil, Canada, Chile, France, Germany, India, Israel, Italy, Japan, Kenya, Mexico, the Netherlands, New Zealand, Nigeria, the Philippines, Singapore, South Korea, the UAE, and the UK.

model weights.

safety, security, and trust

President Biden is convening seven leading AI companies at the White House today – Amazon, Anthropic, Google, Inflection, Meta, Microsoft, and OpenAI – to announce that the Biden-Harris Administration has secured voluntary commitments from these companies to help move toward safe, secure, and transparent development of AI technology.   

desetak godina eksperimentisanja

ollaborative could acquire or develop and then distribute AI systems to address these gaps, poolingresources from member states and international development programs, working with frontier AIlabs to provide appropriate technology, and partnering with local businesses, NGOs, and beneficiarygovernments to better understand technological needs and overcome barriers to use

cquiresand distributes AI systems

institutions taking on the role of several of the models above

ssed by offering safety researchers withinAI labs dual appointments or advisory roles in the Project,

it diverts safety research away from the sites of frontier AI development.

such an effort would likely be spearheaded byfrontier risk-conscious actors like the US and UK governments, AGI labs and civil society groups

ccelerate AI safety researchby increasing its scale, resourcing and coordination, thereby expanding the ways in which AI canbe safely deployed, and mitigating risks stemming from powerful general purpose capabilities

xceptional leaders and governancestructures

an institution with significant compute, engineering capacity and access tomodels (obtained via agreements with leading AI developers), and would recruit the world’s leadingexperts

n AI Safety Project need not be, and should beorganized to benefit from the AI Safety expertise in civil society and the private sector

like ITER and CERN.

conduct technical AI safety research26at an ambitious scale

y to exclude from participation states who are likely to want to useAI technology in non-peaceful ways, or make participation in a governance regime the preconditionfor membership

consistently implement the necessary controls to manage frontiersystem

he Collaborative to have a clear mandateand purpose

diffusing dangerous AI technologies around theworld, if the most powerful AI systems are general purpose, dual-use, and proliferate easily.

would need to significantly promote access to the benefits of advanced AI (objective1), or put control of cutting-edge AI technology in the hands of a broad coalition (objective 2)

he resourcesrequired to overcome these obstacles is likely to be substantial,

nderstanding the needs of membercountries, building absorptive capacity through education and infrastructure, and supporting thedevelopment of a local commercial ecosystem to make use of the technology

being deployed for “protective” purposes

ncrease global resilience to misusedor misaligned AI systems

existence of a technologicallyempowered neutral coalition may also mitigate the destabilizing effects of an AI race betweenstates

access to its safe technology could be offered as an incentivefor countries to participate in a governance regime that enforces responsibility (such as agreementsto enact stricter regulation, or restrict military AI development).

reduce geopolitical instability amidst fierce AI competition among states

ensure the benefits ofcutting-edge AI reach groups that are otherwise underserved by AI developmen

legitimate international access to advanced AI

a Frontier AICollaborative could take the form of an international private-public partnership that leverages existingtechnology and capacity in industry, for example by contracting access to or funding innovation inappropriate AI technology from frontier AI developers.

ligned countries may seek to form governance clubs, asthey have in other domains. This facilitates decision-making, but may make it harder to enlist othercountries later in the process

its effectiveness will depend on its membership, governance and standard-setting processes

Governance Organization should focus primarily on advanced AI systems thatpose significant global risks, but it will be difficult in practice to decide on the nature and sophisti-cation of AI tools that should be broadly available and uncontrolled versus the set of systems thatshould be subject to national or international governance

Automated (even AI-enabled) monitoring

some states may be especially reluctant to join due to fear of clandestinenoncompliance by other states

Other AI-specific incentives for participation include conditioning on participationaccess to AI technology (possibly from a Frontier AI Collaborative) or computing resources.22Statesmight also adopt import restrictions on AI from countries that are not certified by a GovernanceOrganization

while urgent risks may need to be addressed at first by smallergroups of frontier AI states, or aligned states with relevant expertise

The impact of a Governance Organization depends on states adoptingits standards and/or agreeing to monitoring.

standard setting (especially in an international and multistakeholder context) tends to be a slowprocess

detection and inspections of large data centers

self-reporting of compliance with international standards

Where states have incentives to undercut each other'sregulatory commitments, international institutions may be needed to support and incentivize bestpractices. That may require monitoring standards compliance.

therefore enable greater access to advanced AI

international standard setting wouldreduce cross-border frictions due to differing domestic regulatory regimes

uture regulations will limit access to powerful AI technologies in jurisdictions with inadequate AIgovernanc

he InternationalTelecommunication Union (ITU)

Advanced AI Governance Organization.

intergovernmental or multi-stakeholder

as less institutionalizedand politically authoritative scientific advisory panels on advanced AI

epresentation may trade off against a Commission’s ability to overcomescientific challenges and generate meaningful consensus

broad geographic representation in the main decisionmaking bodies, and a predominance of scientificexperts in working groups

he scientific understanding of the impacts of AI should ideally beseen as a universal good and not be politicized

foundational “Conceptual Framework

Commission might undertake activities that draw andfacilitate greater scientific attention, such as organizing conferences and workshops and publishingresearch agenda

o increase chances of success, aCommission should foreground scientific rigor and the selection of highly competent AI expertswho work at the cutting edge of technological development and who can continually interpret theever-changing technological and risk landscape

internationally representative group of experts

there is significant disagreement even among experts about the different opportunities andchallenges created by advanced AI

International consensus on the opportunities and risks from advanced AI

the Commission on Frontier AI could facilitatescientific consensus by convening experts to conduct rigorous and comprehensive assessments ofkey AI topics, such as interventions to unlock AI’s potential for sustainable development, the effectsof AI regulation on innovation, the distribution of benefits, and possible dual-use capabilities fromadvanced systems and how they ought to be managed

intergovernmental body

dangerous inputs: computing resources have been targeted by US, Japanese and Dutch export controlsthat prevent the sale of certain AI chips and semiconductor manufacturing equipment to Chin

norms and standards

standards

Establish guidelines

through education, infrastructure, andsupport of the local commercial ecosystem

develop frontier AI collectively or distribute and enable access

developing and/or enabling safe forms of access to AI.

ontrolling AIinputs

tobuild consensus on risksand how they can be mitigated,andset safety norms and standardsandsupport their implementationto help developers and regulators with responsible developmentand use. International efforts toconduct or support AI safety research

national regulation may be ineffective for managing the risks of AI even within states. States willinevitably be impacted by the development of such capabilities in other jurisdictions

building capacity to benefit from AI through education, infrastructure, andlocal commercial ecosystems

build consensus on AI opportunities

Standards

SO/IEC

whether these institutions should be new or evolutions of existing organizations, whether the con-ditions under which these institutions are likely to be most impactful will obtain,

A failure to coordinate or harmonizeregulation may also slow innovation.

It groups these functions into fourinstitutional models that exhibit internal synergies and have precedents in existingorganizations:

the Media in the Digital Age.

But if the superforecasters are so good at predictions, and experts have so much topic-specific knowledge, you might at least expect the two groups to influence each other’s beliefs.

But superforecasters and AI experts seemed to hold very different views of how societies might respond to small-scale damage caused by AI . Superforecasters tended to think that would prompt heavy scrutiny and regulation to head off bigger problems later. Domain experts, by contrast, tended to think that commercial and geopolitical incentives might outweigh worries about safety, even after real harm had been caused.

Such people share a few characteristics, such as careful, numerical thinking and an awareness of the cognitive biases that might lead them astray.

The emergence of modern, powerful machine-learning models dates to the early years of the 2010s. And the field is still developing quickly. That leaves much less data on which to base predictions.

If humans used AI to help design more potent bioweapons, for instance, it would have contributed fundamentally, albeit indirectly, to the disaster.

One reason for AI ’s strong showing, says Dan Maryland, a superforecaster who participated in the study, is that it acts as a “force multiplier” on other risks like nuclear weapons

The median superforecaster reckoned there was a 2.1% chance of an AI -caused catastrophe, and a 0.38% chance of an AI -caused extinction, by the end of the century. AI experts, by contrast, assigned the two events a 12% and 3% chance, respectively.

A “catastrophe” was defined as something that killed a mere 10% of the humans in the world, or around 800m people. (The second world war, by way of comparison, is estimated to have killed about 3% of the world’s population of 2bn at the time.) An “extinction”, on the other hand, was defined as an event that wiped out everyone with the possible exception of, at most, 5,000 lucky (or unlucky) souls.

On the one hand were subject-matter, or “domain”, experts in nuclear war, bio-weapons, AI and even extinction itself. On the other were a group of “superforecasters”—general-purpose prognosticators with a proven record of making accurate predictions on all sorts of topics, from election results to the outbreak of wars.

These days, worries about “existential risks”—those that pose a threat to humanity as a species, rather than to individuals—are not confined to military scientists. Nuclear war; nuclear winter; plagues (whether natural, like covid-19, or engineered); asteroid strikes and more could all wipe out most or all of the human race. The newest doomsday threat is artificial intelligence ( ai ). In May a group of luminaries in the field signed a one-sentence open letter stating: “Mitigating the risk of extinction from AI should be a global priority alongside other societal-scale risks such as pandemics and nuclear war.”

India insists data must be stored locally: to give its law-enforcement agencies easy access, to protect against foreign snooping and as a way to boost investment in the tech sector.

most governments lack policymakers with relevant technical expertise and most digital issues cut across different domains, extending beyond the traditional remit of trade negotiators.

In 2019 Abe Shinzo, the late Japanese prime minister, proposed the concept of Data Free Flow with Trust. That rather nebulous idea is materialising as a set of global norms to counter digital protectionism. As Matthew Goodman of CSIS, a think-tank in Washington, puts it: “It’s about the un-China approach to data governance.”

“There’s a vacuum in terms of rules, norms and agreements that govern digital trade,” laments Nigel Cory of the Information Technology and Innovation Foundation, a research institute in Washington .