JAV žemės ūkio skatinimo išlaidos auga

„Dėdė Semas planuoja skirti daugiau pinigų nei bet kada anksčiau, kad padėtų palengvinti Amerikos ūkininkų ekonomines problemas.

 

Žemės ūkio departamentas šiais metais apskaičiavo, kad tiesioginės išmokos ūkininkams 2026 m. pasieks 44 mlrd. USD. Tai reiškė, kad vyriausybės išmokos gali sudaryti daugiau nei ketvirtadalį prognozuojamų grynųjų ūkių pajamų, kurios yra ūkininkų pelno matas [1].

 

Tai buvo dar prieš tai, kai prezidentas Trumpas trečiadienį paprašė Kongreso patvirtinti 11 mlrd. USD finansavimą, daugiausia skirtą padėti ūkininkams susidoroti su karo su Iranu padariniais. Jei bus patvirtinta, vyriausybės išmokos ūkininkams šiais metais gali pasiekti rekordinį lygį.

 

Vyriausybės finansavimas per pastarąjį dešimtmetį atliko didesnį vaidmenį remiant ūkių pajamas, įskaitant su prekybos karu susijusias išmokas per pirmąją ir antrąją Trumpo kadencijas; gelbėjimo finansavimą per Covid-19 pandemiją; ir čekius, skirtus padėti ūkininkams susidoroti su mažomis pasėlių kainomis. Šių metų konflikto Artimuosiuose Rytuose metu ūkininkai turėjo išleisti daugiau pinigų kurui, kad galėtų eksploatuoti įrangą, ir trąšoms sodinimui.

 

Ūkininkų prekybos grupės ragino skirti daugiau pagalbos, teigdamos, kad tai gyvybiškai svarbu norint išlaikyti Amerikos žemės ūkį. Tačiau Kai kurie ekonomistai ir pramonės analitikai reiškia susirūpinimą dėl padidintų vyriausybės išmokų, teigdami, kad neaišku, kiek reikia JAV žemės ūkio gamybai išlaikyti.

 

„Ne paslaptis, kad žemės ūkio šalys sunkiai dirba, ir ši laikina ekonominė parama labai padės užtikrinti ūkininkams ekonominį stabilumą, laukiant derliaus nuėmimo sezono“, – sakė Scottas Metzgeris, Amerikos sojų pupelių asociacijos prezidentas ir Ohajo ūkininkas.

 

USDA teigimu, kukurūzus ir sojų pupeles auginantys ūkininkai praėjusiais metais nuėmė vieną didžiausių derlių istorijoje ir šiais metais laukia dar vieno gausaus derliaus. Derlius sukėlė grūdų perteklių, sumažindamas žaliavų kainas ir kartu didindamas ūkių pajamas.

 

Ryžių, medvilnės ir kitų kultūrų augintojai jau daugelį metų susiduria su sunkumais. Galvijų verslas yra šviesus žemės ūkio ekonomikos taškas, nes daugelis rančininkų dėl galvijų trūkumo ganyklose uždirba rekordines sumas.

 

USDA prognozuoja, kad grynosios ūkių pajamos šiais metais iki naujausio pagalbos plano siekė 153,4 mlrd. USD, šiek tiek mažiau nei 2025 m. Tačiau bendra suma bus didesnė. nei 20 metų vidurkis.

 

Vyriausybės išmokos, įskaitant išmokas, skirtas gamtosaugos pastangoms ir socialinės apsaugos programoms, kai pasėlių rinkos kainos nukrenta žemiau tam tikro lygio, greičiausiai padidintų ūkių pajamas.

 

Išmokos padėjo išvengti finansinės krizės ūkių ekonomikoje, išlaikant stabilias pajamas, ir paskatino žemės ūkio paskirties žemės vertės kilimą nepaisant sudėtingos rinkos, teigė Ilinojaus Urbana-Champaign universiteto žemės ūkio ekonomistas Scottas Irwinas. „Mes tapome tikrai priklausomi nuo šių ad hoc išmokų“, – sakė jis. „Tai išgyventi ir tobulėti.“

 

Ūkių ekonomika priklauso nuo vyriausybės ne tik tiesioginėmis išmokomis. Pavyzdžiui, JAV įgaliojimai padeda užtikrinti žaliavų, tokių kaip kukurūzų maišymas į etanolį, paklausą. Kovo mėnesį Trumpo administracija padidino reikiamą sojų pupelių aliejaus kiekį, kuris naudojamas biomasės pagrindu pagamintame dyzeline kure, taip padidindama kainas. Trumpo pareigūnai teigė, kad griežtesnė politika gali padėti ūkininkams išsilaikyti savarankiškai. Išplėstinė biokuro politika galėtų padėti ūkininkams pasinaudoti produktyvumo padidėjimu auginant pasėlius, birželio mėnesį „The Wall Street Journal“ pasauliniame maisto forume sakė žemės ūkio sekretoriaus pavaduotojas Stephenas Vadenas.

 

Kai kurie Ekonomistai ir analitikai teigė, kad vyriausybės parama padeda neefektyviai dirbantiems ūkininkams išlikti versle ir motyvuoja augintojus toliau sodinti daugiau, nei reikia rinkai.

 

„Žemos kainos turi išgydyti žemas kainas“, – sakė Susan Stroud, žemės ūkio analitikė ir rinkos tyrimų bei konsultacijų įmonės „No Bull Agriculture“ įkūrėja. „Galiausiai mes skatiname didesnę gamybą.“

 

Daugelis ūkininkų nenori daugiau vyriausybės čekių, bet negali jų atsisakyti, sakė Chuckas Readas, penktos kartos ūkininkas netoli Prinstono, Ilinojaus valstijoje.

 

Tęstinė vyriausybės parama paskatino prastus taupymo ir išlaidų įpročius tarp vyresnio amžiaus ūkininkų, kurie turėtų taupyti tuo metu, kai žaliavų kainos yra aukštos, sakė 74 metų Readas.

 

„Manau, kad jie mums labiau pakenkė, nei padėjo“, – sakė jis apie vyriausybės gelbėjimo paketus ūkininkams. „Nors žemės ūkio šalis vis dar palaiko Trumpą, tai yra socializmo reikalai.“ [2]

 

1. Kokią prognozuojamų grynųjų ūkių pajamų, ūkininkų pelno mato, dalį galėtų sudaryti vyriausybės išmokos ES šalyse?

 

Vyriausybės išmokos, daugiausia iš ES bendrosios žemės ūkio politikos (BŽŪP), sudaro vidutiniškai trečdalį (33 %) visų žemės ūkio pajamų visose ES šalyse. Kai kuriems konkretiems ūkių tipams ir regionams šis skaičius reguliariai viršija 50 % pelno.

 

Subsidijos yra labai svarbus stabilizuojantis socialinės apsaugos tinklas, tačiau tiksli jų dalis labai skiriasi priklausomai nuo šalies, ūkio dydžio ir prekės.

 

Subskirstymas pagal šalis

Priklausomybė nuo viešųjų lėšų visoje ES labai skiriasi. Nors šalių lygmens vidurkiai svyruoja priklausomai nuo rinkos sąlygų, istorinių duomenų tendencijos rodo:

 

• Mažesnė priklausomybė (mažiau nei 25 % pajamų): tokios šalys kaip Nyderlandai, Ispanija, Italija, Kipras ir Malta mažiausiai pasikliauja subsidijomis, kad gautų bendras žemės ūkio pajamas.

 

• Didesnė priklausomybė (nuo 40 % iki daugiau nei 50 % pajamų): tokios šalys, kaip Latvija, Lietuva, Estija, Slovakija, Suomija ir Švedija, labai priklauso nuo viešosios paramos. Kai kuriose Šiaurės ir Baltijos šalyse bendros vyriausybės subsidijos tam tikrais metais gali viršyti net 100 % deklaruotų šeimos ūkių pajamų, o tai reiškia, kad ūkiai be jų dirba nuostolingai.

 

Struktūriniai skirtumai

• Pagal ūkio dydį: parama yra labai koncentruota. Maždaug 70 % tiesioginių išmokų skiriama vidutinio dydžio ūkiams (nuo 5 iki 250 hektarų), o dideli ūkiai, turintys daugiau nei 250 hektarų, gauna daugiau nei 20 % išmokų. Priešingai, 1–10 % turtingiausių gavėjų keliose valstybėse narėse gauna neproporcingai didelę visų subsidijų lėšų dalį.

 

• Pagal prekę: Gyvulininkystės sektoriai (ypač jautienos ir avienos) daug labiau priklauso nuo subsidijų, kad išliktų pelningi, palyginti su sodininkystės ar intensyvios gyvulininkystės sistemomis.

2. U.S. News: U.S. Tab to Boost Agriculture Is Rising. Thomas, Patrick.  Wall Street Journal, Eastern edition; New York, N.Y.. 29 June 2026: A4.  

 

 

 

U.S. Tab to Boost Agriculture Is Rising

“Uncle Sam is slated to fork over more money than ever to help ease American farmers' economic woes.

 

The Agriculture Department this year estimated that direct payments to farmers would hit $44 billion in 2026. That meant government payments could account for more than a quarter of projected net farm income, a measure of farmers' profits [1].

 

That was before President Trump on Wednesday asked Congress to approve $11 billion in funding, largely to help farmers deal with effects from the war with Iran. If approved, government payments to farmers this year could reach a record.

 

Government funding has played a bigger role supporting farm incomes over the past decade, with trade war-related payouts during Trump's first and second terms; rescue funding through the Covid-19 pandemic; and checks to help farmers deal with low crop prices. During this year's conflict in the Middle East, farmers have had to shell out more cash for fuel to run equipment and fertilizer for planting.

 

Farmers' trade groups have pushed for more aid, saying it is vital to keep American agriculture afloat. But some economists and industry analysts are raising concerns about the stepped-up government payments, saying it isn't clear how much is required to maintain U.S. agricultural production.

 

"It is no secret that farm country is struggling, and this temporary economic support will go a long way to provide farmers with economic stability as we look forward to the harvest season," said Scott Metzger, president of the American Soybean Association and an Ohio farmer.

 

Farmers growing corn and soybeans had one of the largest harvests in history last year and are on pace for another bumper crop this year, the USDA said. The harvests have fueled a grain glut, pushing commodity prices down and farm income along with it.

 

Planters of rice, cotton and other crops have struggled for years. The cattle business has been a bright spot for the farm economy with many ranchers hauling in record sums owing to a shortage of cattle on pastures.

 

Net farm income was estimated to be $153.4 billion this year before the latest aid plan, slightly down from 2025 levels, the USDA has forecast. But the total would be higher than the 20-year average.

 

The government payments, including those for conservation efforts and safety-net programs when market prices for crops fall below certain levels, would likely prop up farm income.

 

The payments helped stave off a financial crisis in the farm economy by keeping incomes stable and spurred a run-up in valuations of farmland despite the difficult market, said Scott Irwin, an agricultural economist at the University of Illinois Urbana-Champaign. "We've become really addicted to these ad hoc payments," he said. "It's survive and advance."

 

The farm economy relies on the government in ways beyond direct payments. For example, the U.S. mandates help guarantee demand for commodities, such as corn being blended into ethanol. In March, the Trump administration increased the required amount of soybean oil that goes into biomass-based diesel fuel, boosting prices. Trump officials have said stronger policies can help farmers stand on their own. Expanding policies regarding biofuels could help farmers benefit from gains in productivity in raising crops, Deputy Agriculture Secretary Stephen Vaden said at The Wall Street Journal's Global Food Forum in June.

 

Some economists and analysts said the government aid is keeping inefficient farmers in business and motivating growers to keep planting beyond what the market needs.

 

"Low prices have to cure low prices," said Susan Stroud, an agriculture analyst and founder of No Bull Agriculture, a market research and consulting firm. "What we're doing is ultimately encouraging more production."

 

Many farmers don't want more government checks but can't turn them down, said Chuck Read, a fifth-generation farmer near Princeton, Ill.

 

Continued government support has motivated poor savings and spending habits among older farmers who should be saving during times when commodity prices are high, said Read, 74 years old.

 

"I think they've hurt us more than they've helped us," he said about government bailouts to farmers. "Even though farm country is pro-Trump still, this is socialism stuff."” [2]

 

 

1. How big part of projected net farm income, a measure of farmers' profits, could government payments in EU countries account for?

 

Government payments—primarily from the EU’s Common Agricultural Policy (CAP)—account for an average of one-third (33%) of total agricultural income across EU countries. For some specific farm types and regions, this figure regularly exceeds 50% of profits.

Subsidies act as a crucial stabilizing safety net, but their exact proportion varies significantly depending on the country, farm size, and commodity.

Breakdown by Country

Dependence on public funds varies widely across the EU. While country-level averages fluctuate based on market conditions, historical data trends show:

•          Lower dependency (under 25% of income): Countries like the Netherlands, Spain, Italy, Cyprus, and Malta rely least on subsidies for overall agricultural income.

 

•      Higher dependency (40% to over 50% of income): Countries like Latvia, Lithuania, Estonia, Slovakia, Finland, and Sweden heavily rely on public support. In some Nordic and Baltic states, total government subsidies can even surpass 100% of reported family farm income in certain years, meaning the farms operate at a loss without them.

 

Structural Variations

•          By Farm Size: Support is heavily concentrated. Roughly 70% of direct payments go to medium-sized farms (5 to 250 hectares), while large farms with over 250 hectares account for over 20% of payments. Conversely, the top 1% to 10% of wealthiest recipients claim a disproportionately large share of total subsidy funds in several member states.

•          By Commodity: Livestock sectors (particularly beef and sheep) have a much higher reliance on subsidies to remain profitable compared to horticulture or intensive livestock systems.

2. U.S. News: U.S. Tab to Boost Agriculture Is Rising. Thomas, Patrick.  Wall Street Journal, Eastern edition; New York, N.Y.. 29 June 2026: A4.  

 

 

 

China Resets AI Race With U.S. As Security Models Mark Gains --- Advances intensify industry worries over White House barriers to developer releases

 

 

“Chinese artificial-intelligence systems have matched the performance of Anthropic's Mythos model in some cybersecurity scenarios, a development poised to reset the global tech race and pressure the White House over its overhaul of U.S. AI policy.

 

Security researchers said that a new AI model, released this month by China's Zhipu AI, also known as Z.ai [1], can match the latest U.S. models when it comes to finding security bugs, although it still lags behind Anthropic's and OpenAI's products in other tasks.

 

Overall, the capability gap between top U.S. models and those built by Chinese companies has narrowed significantly, and use of Chinese AI systems has surged as businesses seek to rein in runaway costs. A host of companies, including Microsoft, are weighing how they can offer Chinese models on their platforms, a development that is set to alter the balance of power among tech companies.

 

"China is making sure that the gap becomes smaller and smaller over time," said Lior Div, chief executive officer of cybersecurity company 7AI.

 

The ability of AI systems to find bugs in software has added urgency to efforts to use models to close vulnerabilities that could be exploited by hackers. Otherwise, the world will face what some researchers call a bugmageddon.

 

Unlike models from Anthropic or OpenAI, Zhipu's GLM-5.2 is open-weight. That means it can be downloaded and run on hardware operated by anybody and can be modified and used without supervision.

 

Open-weight models are ideal for users who want unfettered access to systems they control, but they are also ideal for hackers, who can run them in the shadows.

 

GLM-5.2 has ranked as one of the 10 most-used AI models, according to data from OpenRouter, a company that provides access to more than 400 AI models.

 

In some tests, says the cybersecurity company Semgrep, GLM-5.2 bested Anthropic's Claude Opus 4.8 model, which was released in May.

 

When given further instructions, Opus 4.8 and GLM-5.2 can match Mythos in bug-finding ability, researchers said.

 

Last week, Chinese cybersecurity company 360 Security Technology released a new bug-finding tool called Tulongfeng. The company said it was comparable to Mythos in finding bugs. Those capabilities have alarmed many national-security officials and CEOs.

 

"This kind of powerful weapon that can alter the landscape of cyberwarfare can't remain solely in American hands," 360 Security Chief Executive Zhou Hongyi said at a conference in Beijing.

 

Zhou, an internet veteran and member of China's top political advisory body, said China would face unacceptable risks if U.S. entities could use advanced AI models to scan critical Chinese network systems while denying Chinese companies comparable capabilities.

 

China's advances coincide with U.S. roadblocks to developers releasing models.

 

On Friday, OpenAI said it was limiting access to its latest model, known as GPT-5.6, because of security concerns among administration officials.

 

The company warned that the current case-by-case model-evaluation process wasn't a long-term solution but said it is being used while a recent executive order focused on security and model oversight is implemented.

 

One of Anthropic's latest general-use models has been shut down for more than two weeks after the Trump administration said no foreign entity or individual could use it because of security risks. The company closed all access to comply with the rule.

 

Fable 5, a general-purpose version of Anthropic's powerful Mythos model that was also banned, remains restricted, and restrictions on Mythos 5 still apply to entities that aren't trusted partners.

 

Many have called the administration's stance against a leading U.S. AI company counterproductive and criticized its decision to allow exports of AI chips to China in light of the nation's recent advances.

 

"Banning Fable while selling chips China needs to develop its own version is a gift to China," said Saif Khan, a distinguished technology fellow at the Institute for Progress think tank who worked on export restrictions in the Biden administration. The U.S. needs to maximize the use of Mythos and comparable models to harden its cyber defenses while it can, he added.

 

Among the Mythos 5 and Fable 5 users that had lost access before Friday's decision to restore Mythos 5 access for some trusted entities: the National Security Agency, which had been testing the tools and found them impressive in trials, people familiar with the matter said.

 

Critics of the White House approach have said it has been lax in restricting use of Chinese open-weight models from companies such as DeepSeek and Zhipu, which are popular among U.S. businesses.

 

Some companies have evaded existing chip-export restrictions, while others have used distillation -- in which a new system learns from an existing one by asking it hundreds of thousands of questions and analyzing the answers -- to benefit from U.S. advances.

 

"Our administration is very much focused on Chinese open-source models," said Jacob Helberg, who is undersecretary of state for economic affairs. "It's something that we're tracking very closely."

 

In one sign the administration wants to boost U.S. open-weight companies, the Pentagon recently announced a deal with one of the few domestic open-weight developers, Reflection AI, for use in classified settings along with a host of similar agreements.

 

David Sacks, a White House AI adviser and venture capitalist who advocates for open-source models and an industry-friendly tech strategy, said on X Sunday that China's advances justify Trump's approach to accelerating model development. "We deviate from that strategy at our peril," he said. Sacks has been pitted against security-minded officials advocating for more AI oversight.

 

At the same time, AI users said U.S. efforts to rein in the worrisome capabilities of recent cybersecurity-focused models have added to concerns that access to needed systems could eventually be cut off.

 

"It is incentivizing companies across the globe to use cheaper but very capable Chinese open-weight models, while at the same time undermining the U.S. AI industry," said Niels Provos, a researcher who led security teams at Google and Stripe. "I don't understand it."” [2]

 

1. Z.ai (formerly known as Zhipu AI outside China) makes its core GLM (General Language Model) models open source.

The company releases its frontier foundation models—such as the GLM-5 and GLM-4 series—with open weights under the permissive MIT License.

Here are a few quick facts about Z.ai's open-source offerings:

 

•     Top-Tier Performance: The flagship GLM-5 models perform at the level of leading proprietary AI models, specifically excelling in coding and autonomous agent workflows with a 1 million token context window.

 

•     Where to find them: The model weights are freely available on Hugging Face.

 

•           API Access: You can also access the models via developer platforms like OpenRouter or directly through Z.ai's Developer Docs.

 

•     You can deploy these models locally, keeping all your secrets safe.

 

2. China Resets AI Race With U.S. As Security Models Mark Gains --- Advances intensify industry worries over White House barriers to developer releases. McMillan, Robert; Huang, Raffaele; Ramkumar, Amrith.  Wall Street Journal, Eastern edition; New York, N.Y.. 29 June 2026: A1.  

From enthusiasm to responsibility: what every organization needs to know about AI regulation

Atea advertisement

“Imagine: a hospital entrusts the heating system to artificial intelligence, but one day it makes a mistake, and all the patients feel it. Who would be responsible for this mistake, how to avoid such situations and what legal consequences would await if damage were caused? As artificial intelligence solutions rapidly penetrate various areas of life and affect ever larger groups of people, these questions are becoming increasingly relevant. Therefore, the European Union adopted the EU Artificial Intelligence Act. Some of its provisions have already entered into force, others will come into force in the coming years. Violations of the legal act will be subject to fines in the millions. So what is important for every organization to know about this regulation and how to prepare for it?

 

Technology lawyer, attorney and partner at the law firm TRINITI JUREX Aurelija Rutkauskaitė claims that the EU AI Act is special in that it is the first time that an attempt is made to regulate the technology itself, and not just its use. consequences. “Until now, it has been said that legal acts must be neutral to technology. However, in the case of the AI ​​Act, the EU is trying to control this important technology, because its impact on humanity is comparable to the emergence of the steam engine or the Internet,” the lawyer emphasizes.

 

According to the expert, the essence of the legal act is to protect human rights and at the same time not to stop technological progress.

Prohibited practices – assessment of employees’ emotions

 

The EU AI Act enters into force in certain stages and parts. The two parts of the legal act that have already entered into force are the most relevant for society and business. “One of them is related to employees’ AI literacy. Organizations are obliged to ensure that employees have a sufficient level of AI literacy, i.e. understand the possibilities and legal risks of the technology,” explains A. Rutkauskaitė.

 

Provisions on prohibited practices are also already in force, for example, AI solutions cannot be used for social ranking or assessment of employees’ emotions. “Such practices are not as far-fetched as they may seem at first glance. For example, a call center uses AI solutions to assess the quality of employees’ conversations with customers. The threshold when emotions are assessed from the timbre of the voice is not far away,” the lawyer claims.

 

Other provisions of the AI ​​Act will come into force later: some in August 2026, some in August 2027. Organizations will have to assess which of the risk levels their AI activities are assigned to. “Risks are divided into four levels. In addition to the already discussed prohibited practices, high, limited and minimal risk practices are distinguished. Obligations arise according to these risk levels – from the lowest to the highest,” the technology lawyer points out.

 

A. Rutkauskaitė also draws attention to the fact that the AI ​​Act applies to the entire life cycle chain of an AI product or solution: both to developers, importers and users, with the exception of so-called household users who use AI for their personal purposes. “However, if I came to work with my Chat GPT in my pocket, I cannot use it for work purposes. The use of AI at work must be defined and regulated,” warns the lawyer.

Importance for the public sector

 

Although the AI ​​Act applies to all organizations, A. Rutkauskaitė emphasizes that its impact may be even greater in the public sector. “Decisions of public sector organizations affect large groups of people or socially more vulnerable individuals: from healthcare or education to the administration of public services or critical infrastructure,” she says. Therefore, it is the public sector that may be subject to stricter requirements for documentation and control, and may also require greater human intervention, more safeguards and clarity.

 

It should also be remembered that public sector organizations will not only have to comply with the requirements of the AI ​​Act themselves, but some of them will also be responsible for supervising the implementation of this act. Here, responsibilities are shared by several institutions. The Innovation Agency helps businesses and the public sector prepare for the entry into force of the AI ​​Act, while the Communications Regulatory Authority will supervise existing AI solutions and their compliance.

 

“However, it does not end there: the State Consumer Rights Protection Service, data protection institutions, medical or children's rights supervision institutions will also be involved within their competence. AI issues will affect many areas,” explains the lawyer.

 

Old responsibilities have not disappeared

 

A. Rutkauskaitė reminds that the AI ​​Act is not the only legal act that organizations must comply with when it comes to AI solutions. “It is possible that problems will arise for organizations not so much because of the AI ​​Act, but because of the excessively irresponsible use of technologies when viewed through other areas of legal regulation. Data protection, intellectual property or public procurement requirements have not “disappeared” anywhere. For example, if an AI solution violates the GDPR or consumer rights, there will certainly be legal liability under the legislation in these areas,” she says.

 

Intellectual property rights may also require special attention.  “For example, if a university makes an invention using AI, copyright protection does not necessarily arise automatically, because the current regulation recognizes only a person as the author,” the lawyer says about various legal pitfalls.

 

Problems can also arise when entrusting the evaluation of public procurement to an algorithm, which can also be wrong. The dispute that arose would then be considered under public procurement law, not the AI ​​Act.

 

The lawyer also provides a real, high-profile example from Lithuanian practice, when one lawyer prepared a cassation appeal using an AI program, but it contained non-existent court cases. “This and other examples show how important it is to keep a person in the decision-making chain, there is even a term in English called “human in the loop”. AI cannot be used without critical assessment,” she warns.

 

 

Ginta Kirkutė, Head of Process Automation at Atea, agrees. “Only when organizations start working with large language models do they see their limits. While organizations only read the headlines, AI seems infallible. However, in practice, it turns out that it can lie with certainty. This creates a more realistic expectation: AI quickly generates drafts, but fact-checking is a human responsibility,” notes the Atea expert.

Has anyone read the Copilot Terms of Use?

 

A. Rutkauskaitė says that one of the most common mistakes in organizations when implementing AI solutions is overconfidence in the technology and too little attention to the conditions of its use. “A simple example is that employees start using Copilot or another AI tool, but does anyone read the terms of use? "Do they even ask what check mark should be checked so that the system does not learn from your information," the lawyer asks.

 

According to her, employees often think that they are talking to a "black hole" and do not realize that they are actually transferring information to a specific technology company. "If we upload confidential documents or personal data to an AI system, we lose control over them. And the responsibility lies not with the developer of the technology, but with the organization that used it," she says.

 

Another common mistake is insufficient attention to data quality. If the AI ​​learning base is collected from anywhere, if it is "dirty" or illegally obtained, the technology can provide incorrect decisions or cause legal problems. Documentation is no less important. "If an organization develops or implements an AI solution, it must be clear how it was developed and what data it was trained on," emphasizes A. Rutkauskaitė.

 

The Atea expert notes that organizations' expectations regarding AI are often much higher than the actual capabilities of the technology. “We are currently seeing a kind of market maturity stage. The initial euphoria and hype are being replaced by a practical understanding of what AI can actually do and where it still gets stuck,” says G. Kirkutė

 

According to her, at first many organizations expected AI to become a kind of “magic button” that would solve business problems on its own, but in fact AI is the second, not the main pilot. The quality of the results depends largely on the accuracy of the query, and human quality control still remains necessary.

Sharing of responsibility between the AI ​​supplier and the user

 

Lawyer A. Rutkauskaitė also draws attention to the sharing of responsibility between the supplier and the user. “A supplier who develops or distributes an AI solution must provide very clear usage guidelines: how the technology can be used and in what cases it is appropriate. If the organization uses the solution as intended, the responsibility remains with the supplier. However, if the technology is applied for a completely different, let’s say, bad purpose, the user is responsible for the consequences,” she explains.

 

Therefore, AI projects will inevitably mean more documents, contracts and issues of responsibility sharing. “Organizations will have to not only implement the technology, but also assess its supplier, security, and compatibility with data protection requirements. Often, technology is purchased without even checking whether the supplier is reliable, whether the system is secure, or whether it can be used for a specific purpose at all,” warns A. Rutkauskaitė.

 

Tips on how to prepare for the AI ​​Act

 

When asked where to start when preparing for the AI ​​Act, A. Rutkauskaitė primarily emphasizes education. “I would start with AI literacy training. It is very important that employees understand how this technology works, what risks it poses and what responsibilities arise when using it,” she says.

 

The next step, according to the expert, is to clearly define the role of the organization. “You need to answer the question: will we just use AI solutions, or will we also develop them ourselves? Duties and responsibilities depend on this. And then you need to set internal guidelines: how do we use the technology, what data can we upload, who supervises the processes,” she explains. In addition, it is very important to follow the recommendations of the responsible state institutions and consult: they promise to actively help organizations prepare.

 

The internal responsibility structure is also important. “It will not necessarily have to be an officer, as in the case of the GDPR, but someone in the organization will have to take on this topic – an IT manager, a security specialist or a compliance team. Organizations often have curious people interested in technology, it may be worth involving them and giving them responsibility,” notes A. Rutkauskaitė.

 

The expert emphasizes that there will be no absolute security in the field of AI, but organizations can become much safer. This requires continuous learning, internal rules and a responsible approach to data and suppliers.

 

“Let’s not have the illusion that the AI ​​Act will be a one-time list of tasks, in which, after doing your homework, you will only have to put ticks. AI regulation will operate in cycles – you will need to constantly assess risks, follow the recommendations of institutions, and check whether our solutions still meet the requirements,” says A. Rutkauskaitė.

 

The most important thing is to understand that technology does not replace human decisions. “The human ability to think is like a map, and artificial intelligence is just a car traveling according to that map,” summarizes G. Kirkutė.”