Dalith Steiger-Gablinger, Co-Founder SwissCognitive – “AI Takes Center Stage at Davos 2025: A SwissCognitive Perspective”

As the snow-capped peaks of Davos played host to the World Economic Forum 2025, the air was thick with excitement and a palpable sense of urgency. This year’s theme, “Collaboration for the Intelligent Age,” set the stage for intense discussions on artificial intelligence (AI) and its potential to reshape our world. As co-founders of SwissCognitive, Andy Fitze and I, Dalith Steiger, had the privilege of being flies on the wall at various public side events, soaking in the insights and debates that unfolded.

The buzz around AI was impossible to ignore, with sessions ranging from “Harnessing AI for Social Innovation” to “The Pulse of AI Innovation”. Clearly, the technology has moved beyond mere hype and into the realm of transformative force. As James Ong, one of the panellists, aptly put it, “We need to rethink the philosophy and the relationship between AI and human beings.” AI is not just a tool; it’s a paradigm shift that will redefine how we work, live, and interact with the world around us.”

“We need to rethink the philosophy and the relationship between AI and human beings.” James Ong, Founder and Director of Artificial Intelligence International Institute [AIII]

One of the most striking aspects of the discussions was the emphasis on collaboration. Gone are the days of siloed AI development. The consensus at Davos was clear: to harness the full potential of AI and ensure its benefits are widely distributed, we need unprecedented levels of cooperation between governments, businesses, and civil society.

Another discussion that deeply resonates with our vision at SwissCognitive is the AI discussion in avoiding the pitfalls of the digital divide, emphasising the need for AI to “lift all boats” rather than exacerbate existing inequalities. We strongly advocated for inclusive AI development.

The ethical implications of AI were another hot topic. The sentiment that we are not just building algorithms; we are shaping the future of humanity was echoed across multiple panels, with discussions ranging from AI’s impact on privacy to its potential to either mitigate or exacerbate climate change.

As we navigated the bustling streets of Davos, Andy and I found ourselves in impromptu discussions with fellow attendees. One of the enlightening discussions was while waiting for the Meta hot chocolate or queuing for the entrance of the Dome. One thing that was present through all our exchanges. People engaged openly, with respect and humour.

The energy was infectious, with everyone from startup founders to policymakers eager to share their perspectives on AI’s future. One conversation that stuck with us was with a young entrepreneur who’s using AI to tackle food waste in developing countries. It was a powerful reminder of AI’s potential to address some of our most pressing global challenges and SDGs.

The governance of AI emerged as a critical theme throughout the forum. With the rapid pace of AI development, there’s a growing recognition that our regulatory frameworks need to evolve just as quickly. The call for adaptive, agile governance structures was loud and clear. We shouldn’t govern 21st-century technology with 20th-century laws!

“We shouldn’t govern 21st-century technology with 20th-century laws!” during a Chatham rules debate

Perhaps the most stimulating discussions, however, centred around the potential of AI to complement human capabilities rather than replace them. AI should be seen as a co-pilot, not an autopilot. As advocates of collaboration between humans and AI, Andy and I were heartened to hear leaders from different sectors emphasise the importance of involving humans in development.

“AI should be seen as a co-pilot, not an autopilot.” during a Chatham rules debate

The Open Source Revolution: A Game-Changer in the Global AI Race

Another topic that consistently emerged in our conversations was the growing importance of open source in AI development. This trend is not just reshaping the technological landscape; it’s also challenging the traditional narrative of national AI supremacy.

The United States’ commitment to investing a staggering $500 billion in AI over the next three years is undoubtedly headline-grabbing. However, as Yann LeCun, VP & Chief AI Scientist at Meta, astutely pointed out during several discussions in Davos, the real story might be the rise of open-source models rather than any single nation’s dominance.

LeCun’s perspective is particularly illuminating: “To people who see the performance of DeepSeek and think: ‘China is surpassing the US in AI.’ You are reading this wrong. The correct reading is: ‘Open source models are surpassing proprietary ones.'”

“Open source LLM models are surpassing proprietary ones.” Yann LeCun, VP & Chief AI Scientist at Meta

This shift towards open source is democratising AI development on a global scale. LeCun explained that “DeepSeek has profited from open research and open source (e.g. PyTorch and Llama from Meta). They came up with new ideas and built them on top of other people’s work. Because their work is published and open source, everyone can profit from it. That is the power of open research and open source.”

Indeed, the open-source movement in AI is gaining momentum rapidly. Models like Llama 2, Mistral, and DeepSeek are not just matching but, in some cases, surpassing the capabilities of proprietary giants like GPT-4 and Google Gemini. This trend is reshaping the AI ecosystem, offering adaptability, cost-efficiency, and privacy compliance that many enterprises find increasingly attractive.

The implications of this shift are profound. While national investments like the U.S.’s $500 billion commitment are crucial, the collaborative nature of open-source development means that innovations can come from anywhere. This global pool of talent and ideas could potentially accelerate AI development far beyond what any single nation or company could achieve alone.

Moreover, the open source movement aligns with the growing calls for AI transparency and accountability. One tech executive at Davos noted, “We’re not just building algorithms; we’re shaping the future of humanity.” Open source development allows for greater scrutiny and collective problem-solving, potentially leading to safer and more ethical AI systems.

“We’re not just building algorithms; we’re shaping the future of humanity.” CEO during a Panel in Davos

As we reflect on the discussions at Davos, it’s clear that the future of AI is not just about who can invest the most money. It’s about fostering a global ecosystem of innovation, collaboration, and shared progress. The rise of open source in AI is not just a technological trend; it’s a paradigm shift that could redefine how we approach some of the world’s most pressing challenges.

In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets but those who can best harness the collective intelligence of the global AI community. As we move forward, it will be fascinating to see how this open-source revolution continues to shape the future of AI and, by extension, our world.

“In this new landscape, the winners will not necessarily be the nations or companies with the deepest pockets, but those who can best harness the collective intelligence of the global AI community.” Andy Fitze, Co-Founder SwissCognitive

As the forum drew to a close, we left Davos with a sense of cautious optimism. The challenges ahead are significant, but so too is the collective will to address them. The conversations made it clear that we are at a pivotal moment in the development of AI, and the decisions we make now will shape its trajectory for years to come. This future belongs to the young generations. We, the older generation, must be aware that every decision we make won’t affect us, as it will affect the younger generations! This responsibility is imperative!

As we return to our work at SwissCognitive, we’re more energised than ever to continue fostering dialogue and collaboration in AI. The insights gained at Davos will undoubtedly inform our efforts to build a future where AI truly lifts all boats, creating a rising tide of innovation and prosperity for all.

“We are the change we wanna see”, Yip Thy Diep Ta, Founder & CEO @ J3D.AI, House of Collaboration

In reflecting on our experience, Andy remarked, “The technical possibilities of AI are astounding, but it’s the human ingenuity in applying these technologies that will truly change the world.” I couldn’t agree more, adding, “AI has the power to amplify our human potential, but only if we approach its development with empathy, wisdom, and a commitment to inclusivity.“

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Copyright: cio.com – “12 AI predictions for 2025”

This year we’ve seen AI move from pilots into production use cases. In 2025, they’ll expand into fully-scaled, enterprise-wide deployments.

Generative AI has seen faster and more widespread adoption than any other technology today, with many companies already seeing ROI and scaling up use cases into wide adoption.

Vendors are adding gen AI across the board to enterprise software products, and AI developers haven’t been idle this year either. We’ve also seen the emergence of agentic AI, multi-modal AI, reasoning AI, and open-source AI projects that rival those of the biggest commercial vendors.

According to a Bank of America survey of global research analysts and strategists released in September, 2024 was the year of ROI determination, and 2025 will be the year of enterprise AI adoption.

“Over the next five to 10 years, BofA Global Research expects gen AI to catalyze an evolution in corporate efficiency and productivity that may transform the global economy, as well as our lives,” says Vanessa Cook, content strategist for Bank of America Institute.

Small language models and edge computing

Most of the attention this year and last has been on the big language models —  specifically on ChatGPT in its various permutations, as well as competitors like Anthropic’s Claude and Meta’s Llama models. But for many business use cases, LLMs are overkill and are too expensive, and too slow, for practical use.

“Looking ahead to 2025, I expect small language models, specifically custom models, to become a more common solution for many businesses,” says Andrew Rabinovich, head of AI and ML at Upwork. LLMs aren’t just expensive, they’re also very broad, and not always relevant to specific industries, he says.

“Smaller models, on the other hand, are more tailored, allowing businesses to create AI systems that are precise, efficient, robust, and built around their unique needs,” he adds.[…]

Read more: www.cio.com

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SwissCognitive Guest Blogger: Zachary Amos – “How AI-Powered Drones Could Fight Wildfires”

With climate change driving hotter, drier conditions, wildfire prevention has become more urgent than ever. Wildfires destroy ecosystems, endanger lives and release massive carbon emissions that worsen global warming. Autonomous drones with AI emerge as an innovative tool to tackle this threat by offering early detection and rapid response capabilities.

High-tech sensors and real-time data allow AI-driven devices to scan expansive, hard-to-reach landscapes. They can spot smoke signals early, analyze environmental risk factors and predict areas most vulnerable to fires. This innovative approach empowers authorities and communities with faster, more accurate prevention tools that promise safer outcomes for people.

Early Smoke Detection

AI-powered drones address a critical weakness in traditional smoke surveillance methods. Conventional practices often struggle with low accuracy and miss early signs of smoke that is transparent or without clear edges. In contrast, these intelligent tools monitor vast, hard-to-reach landscapes. They use advanced sensors to track air quality and temperature shifts that can indicate a fire’s first stages.

Unlike human surveillance — which has limited reach — AI-driven drones identify subtle anomalies in smoke patterns and pinpoint potential fire locations that might otherwise go unnoticed. With real-time data transmission, these devices alert authorities and enable a rapid response to contain fires before they escalate.

Identifying High-Risk Areas

AI drones analyze critical factors like vegetation density, moisture levels and drought conditions to identify higher-risk areas. They use advanced sensors to collect detailed environmental data and flag locations where dense, dry vegetation and prolonged drought create ideal fire conditions.

This insight helps forest services craft smarter prevention strategies, from clearing overgrown brush to focusing monitoring efforts where it matters most. Moreover, these drones improve risk analysis over time with machine learning algorithms that continuously adapt to seasonal and environmental shifts. This approach to data analytics allows organizations to make well-informed decisions and strategically deploy resources to protect vulnerable landscapes.

Monitoring Lightning Strikes

Drones track lightning strike patterns and focus on recently hit areas. This is a crucial approach since lightning remains one of the top causes of wildfires across the 3 trillion trees on Earth. They can spot even the smallest flare-ups with infrared sensors — regardless of harsh weather conditions — which helps them from growing into uncontrollable blazes.

Acting quickly after a lightning strike is essential, and drones make that possible by instantly sending alerts to fire teams when they detect heat anomalies. Authorities can use this technology to respond swiftly and safeguard forests and communities from the devastating impact of wildfires.

Delivering Fire Suppression Supplies

Drones can autonomously deliver fire retardants, water, and other supplies to remote areas that are challenging or dangerous for ground crews to access. These devices use AI algorithms to analyze fire spread patterns, wind conditions and terrain to make precise, targeted drops where they’re most effective.

This capability mirrors the e-commerce industry’s success, where drones completed over 660,000 delivery flights between 2019 and 2022, showcasing the reliability of this transport method in real-world scenarios. Reaching early-stage fires swiftly and efficiently allows these devices to tackle potential wildfire threats before they escalate. They offer a proactive approach that protects natural areas and nearby communities.

Mapping Safe Evacuation Areas

Drones with AI create updated evacuation maps based on real-time analysis of fire spread. This tool is essential in protecting the over 115 million people in the U.S. living in high-risk wildfire counties. Predicting fire movement patterns helps drones pinpoint areas in imminent danger and alert communities. It ensures evacuations are timely and directed toward the safest routes.

These dynamic, drone-generated maps offer critical support to first responders and residents because they adapt to shifting fire lines and environmental changes. Access to accurate, real-time evacuation maps can be lifesaving for those in wildfire-prone areas. They guide residents away from harm’s path with clear, updated information.

Expanding AI-Driven Solutions for a Safer Environment

The potential for integrating AI-driven drones into wildfire prevention strategies is vast. They offer powerful tools to protect ecosystems and safeguard communities at risk. Staying informed about AI and autonomous technology advancements opens doors to supporting and participating in the next wave of environmental protection innovations.

About the Author:

Zachary Amos is the Features Editor at ReHack, where he writes about artificial intelligence, cybersecurity and other technology-related topics.

Der Beitrag How AI-Powered Drones Could Fight Wildfires erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: informationweek.com – “Reducing the Environmental Impact of Artificial Intelligence (AI)”

By adopting energy-efficient architectures, optimizing AI models for performance, and pushing for cloud providers to embrace renewable energy, businesses can help reduce the carbon footprint of their AI solutions.

Artificial intelligence is reshaping our world. Its transformative power fuels innovation across industries — delivering new value to organizations and consumers alike. As the proliferation of AI accelerates, people are starting to ask important questions: How does AI impact the environment? And furthermore, how do we keep pushing for progress without leaving a heavy carbon footprint on the planet? 

AI’s Eco Impact

Artificial intelligence software runs in data centers that consume large amounts of energy and often cause significant carbon emissions. According to Bloomberg, there are more than 7,000 data centers worldwide. Collectively, they can consume as much power annually as the entire electricity production of Australia or Italy. The growing use of AI will further increase this already substantial energy consumption of data centers. 

The use of AI can be separated into two main tasks: training and inferencing. During training, AI models learn from vast amounts of data that can take months depending on data complexity and volume. Once an AI model has been trained, it consumes energy each time it generates a new response or “inference.” The International Energy Agency (IEA) has reported a ChatGPT inquiry requires up to 10 times the electricity of a Google search to respond to a typical request. This energy consumption adds up and can quickly surpass the energy used for training.

The WEF estimates training comprises about 20% of an AI model’s overall energy use across its lifespan, while inferencing makes up the remaining 80%.[…]

Read more: www.informationweek.com

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SwissCognitive Guest Blogger: Vishal Kumar Sharma – “Analysing the Importance of Artificial Intelligence and Robotics in Agriculture”

Introduction

As the foundation of human civilization, agriculture is undergoing a revolution right now. The agriculture sector faces hitherto unheard-of challenges given the rising world population and growing effects of climate change. Though throughout has proven successful, conventional agricultural methods are failing to meet the demands of modern society. Two innovative technologies poised to transform our farming, monitoring, and collecting of crops are artificial intelligence (AI) and robotics. The article investigates the reasons behind the necessity of artificial intelligence (AI) and robotics into agriculture rather than just a passing trend.

The challenge is supplying food for a population growing

By year 2050, the world’s population is expected to reach 10 billion. Feeding this many people calls for a 70% increase in food output, claims the Food and Agriculture Organization (FAO). Still, the resources needed for agriculture land, water, labor are few and in many cases declining. Conventional methods usually damage the environment and demand a lot of human effort. Thus, it is quite necessary to improve farming’s efficiency, sustainability, and output.

The Significance of Artificial Intelligence (AI) in Agriculture

In agriculture, artificial intelligence is the use of data-based, more intelligent decisions making. Large amounts of data in real-time analysis made possible by AI-driven systems gives farmers insightful information that may be utilized to monitor soil condition and project crop harvests. Using satellite images and weather data, artificial intelligence systems can predict ideal planting times, spot disease outbreaks, and suggest effective pest control tactics. Such a great degree of accuracy can lead to notable increases in waste reduction, crop output, and the limitation of the usage of harmful pesticides.

Furthermore, artificial intelligence powered instruments have the capacity to improve resource use efficiency. Precision agriculture driven by artificial intelligence helps farmers to precisely apply pesticides, fertilizers, and water in ideal amounts and targeted areas. This method solves the entwined problems of sustainability and financial viability by lowering costs and mitigating the negative effects of agriculture.

The Significance of Robotics in Agriculture

By automating tasks requiring a lot of manual work, robotics improves artificial intelligence and hence increases farming’s productivity and scalability. Robots are used gradually for harvesting, weeding, and planting jobs. While robotic harvesters can pick fruits and vegetables with no damage, a task difficultly accomplished with human workers, autonomous tractors can plow fields with perfect accuracy. In fields without personnel or where agricultural chores demand great physical effort, this technique is very important.

Precision farming depends much on robotic tools. With sensors and cameras, unmanned aerial vehicles can monitor crop conditions from above and provide current data that lets farmers make wise decisions. Terrestrial robots can do complex tasks including weed removal, therefore reducing the need for herbicides. These technologies not only increase output but also reduce the boring character of manual farming, so appealing agriculture is to younger generations.

Sustainability and environmental impact

Using robotics and artificial intelligence in agriculture has a clear advantage since it helps farming methods to be more sustainable. Often requiring resources, traditional agricultural techniques can lead to soil degradation, water shortage, and a decline in biodiversity. Artificial intelligence (AI) driven analytics can give farmers direction on using sustainable practices such crop rotation, minimum soil disturbance, and irrigation optimization. By enabling precise farming techniques that cut waste and environmental effect, robotics can help to forward this goal.

Artificial intelligence might, for instance, look at soil moisture data and project irrigation needs, therefore ensuring the effective use of water. By selectively distributing fertilizers and pesticides, robots can help to lower the overall consumption and thereby minimize the flow into nearby ecosystems. By maintaining soil health and biodiversity, these technologies not only protect the surroundings but also raise agricultural output.

Advantages in the field of economics

In the context of agriculture, artificial intelligence (AI) and robotics provide clear financial benefits. For farmers, these technologies could help to lower costs, increase crop output, and raise the quality of agricultural goods. By means of predictive capabilities of artificial intelligence, farmers may efficiently reduce risks related to market volatility, pests, and weather conditions, so promoting more stable income. By automating chores requiring a lot of physical labor, robotics can significantly cut labor costs. In places where agricultural labor is either scarce or highly expensive, this is particularly helpful.

Moreover, the information generated by robotics and artificial intelligence can provide farmers with other revenue streams. For example, precise information on crop quality could be used to negotiate better prices or enter special markets. Furthermore, the application of these technologies can improve farming output, therefore raising its competitiveness and maintaining the livelihoods of farmers in both developed and underdeveloped countries.

Challenges and the road forward

Though robots and artificial intelligence (AI) have great potential in agriculture, several factors prevent their general application. Mostly because of high startup costs, lack of technology knowledge, and concerns about data privacy, smallholder farmers in underdeveloped areas have great difficulties. Governments, research labs, and businesses must cooperate to provide training, subsidies, and support systems that make this technology available to all farmers thereby overcoming these challenges.

Moreover, the development of robotics and artificial intelligence in agriculture has to be guided by ideas of durability and fairness. It is imperative to ensure that these technologies benefit smallholder farmers, the basis of world food supply, as well as big-scale commercial farms as they develop.

Conclusion

Rather than only a technical development, artificial intelligence and robots are essential tools for the direction of agriculture. These technologies offer a way to reach a more efficient, ecologically friendly, and flexible agricultural system within the worldwide fight to solve the problems of feeding an increasing population and preserving the environment. Including robotics and artificial intelligence (AI) into agricultural practices has moved from a luxury to a necessary need. These technologies will help us to ensure that agriculture meets the needs of the present generation without endangering the capacity of next generations to support themselves.

References:

1. Food and Agriculture Organization (FAO). (2017). The future of food and agriculture: Trends and challenges.
2. Aravind, K. R., Raja, P., & McKee, G. (2017). A review of agriculture robotics: Current trends and future directions. Computers and Electronics in Agriculture, 142, 379-394. doi:10.1016/j.compag.2017.09.030
3. Shamshiri, R. R., Kalantari, F., Ting, K. C., et al. (2018). Advances in greenhouse automation and controlled environment agriculture: A transition to plant factories and urban agriculture. International Journal of Agricultural and Biological Engineering, 11(1), 1-22. doi:10.25165/j.ijabe.20181101.3790
4. Wolfert, S., Ge, L., Verdouw, C., & Bogaardt, M. J. (2017). Big data in smart farming – A review. Agricultural Systems, 153, 69-80. doi:10.1016/j.agsy.2017.01.023
5. Balafoutis, A., Fountas, S., Cavalaris, C., et al. (2017). Precision Agriculture Technologies Positively Contributing to GHG Emissions Mitigation, Farm Productivity and Economics. Sustainability, 9(8), 1339. doi:10.3390/su9081339
6. Zhang, C., & Kovacs, J. M. (2012). The application of small unmanned aerial systems for precision agriculture: A review. Precision Agriculture, 13(6), 693-712. doi:10.1007/s11119-012-9274-5

About the Author:

Vishal Kumar Sharma, Senior Project Engineer of AI Research Centre, Woxsen University, India, with over 8 years of experience in team management, PCB design, programming, robotics manufacturing, and project management. He has contributed to multiple patents and is passionate about merging smart work with hard work to drive innovation in AI and robotics.

Der Beitrag Analysing the Importance of Artificial Intelligence (AI) and Robotics in Agriculture erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

Copyright: technologyreview.com – “Why Artificial Intelligence (AI) and Clean Energy Need Each Other”

We are in the early stages of a geopolitical competition for the future of artificial intelligence. The winners will dominate the global economy in the 21st century.

Der Beitrag Why Artificial Intelligence (AI) and Clean Energy Need Each Other erschien zuerst auf SwissCognitive | AI Ventures, Advisory & Research.

AI Investments in the Spotlight – SwissCognitive AI Investment Radar

OpenAI’s $6 billion funding round stands out, showcasing investor confidence as the company targets a $150 billion valuation. Meanwhile, BlackRock and Microsoft are setting the stage for large-scale AI infrastructure with a $30 billion fund to fuel data centers and energy projects, further cementing AI’s role in global development.

Investors are increasingly drawn to specialized AI applications built on open-source models, as seen at this year’s AI Summit. Financial advisors and venture capitalists alike are placing AI at the top of their investment priorities, with U.S. VCs leading the charge in comparison to their global counterparts. In India, Google and Nvidia are expanding their AI initiatives, underscoring the region’s importance in the broader AI narrative.

As AI continues to intertwine with sustainability goals, we also see a growing interest in how AI can address global challenges such as climate change and resource management, with investors keeping a keen eye on the potential of AI to advance the UN’s Sustainable Development Goals. Alongside this, partnerships between nations like the UAE and U.S. demonstrate the strategic push to leverage AI for mutual growth in technology and economic development.

Join us as we delve deeper into the key developments and insights shaping AI investments this week, from groundbreaking megadeals to emerging opportunities that are set to drive the next phase of AI-driven innovation.

Previous SwissCognitive AI Radar: AI Funds, Energy Needs, and Tech Giants.

Our article does not offer financial advice and should not be considered a recommendation to engage in any securities or products. Investments carry the risk of decreasing in value, and investors may potentially lose a portion or all of their investment. Past performance should not be relied upon as an indicator of future results.

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Copyright: businesstimes.com.sg – “The Paradox Of Decarbonising AI”

AI can bring untold benefits such as optimised energy use but guzzles a lot of water and power. The paradox can be tackled by aligning AI development with green practices.

Artificial Intelligence (AI) holds immense potential to drive decarbonisation, by offering revolutionary benefits such as optimised energy consumption and speeding up the deployment of renewable energy.

However, this potential is not without its challenges, because running AI operations entails the substantial use of energy and water – a paradox which puts investors in sustainable practices in a difficult position, given that they must balance the push for AI-driven transformation with the risk of increased carbon emissions if AI systems are not sustainably powered.

In the realm of investing, this issue has intensified. Investors face the dual burden of decarbonising investment portfolios while ensuring profitability. Explicit emissions targets or “budgets” often require rebalancing portfolios to stay within set carbon limits. Yet, as investments in AI technologies grow, so will the complexity of managing their environmental impact.

Environmental impact

Training and operating advanced AI models consume enormous amounts of energy. The International Energy Agency (IEA) has noted that a single Google search consumes 0.3 watt-hours of electricity, but a ChatGPT request requires 2.9 watt-hours – pointing to the large difference in computational expense.

But while both figures appear small in isolation, there are profound environmental implications at scale.

Companies across industries are rapidly integrating AI for diverse applications, ranging from customer-service chatbots to AI-powered analytics tools that boost efficiency and decision-making. For instance, in Singapore, an AI utility was launched to combat greenwashing by using nationwide green building to support decisions on sustainability-linked loans.[…]

Read more: www.businesstimes.com.sg

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Explore the AI news in this week’s spotlight:

AI’s role in diplomacy enhancing global negotiations
Liverpool using AI to sharpen their corner kicks
AI tackles global challenges from climate change to sustainability
48% of healthcare organizations using AI to combat cyber risks
Google against AI-generated deepfakes
… and more!

Happy reading and #ShareForSuccess!

Kind regards from sunny Zürich,

The Team of SwissCognitive

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Copyright: ohchr.org – “Artificial Intelligence (AI), a game-changer for sustainable development”

“Unprecedented advances in digital technology, including generative Artificial Intelligence, offer us previously unimaginable opportunities to move forward on the enjoyment of human rights and contribute to rescuing the 2030 Agenda,” said UN Human Rights Chief Volker Türk in his vision statement,  “Human Rights: A Path for Solutions.”

AI was the main spotlight at the fifth annual AI for Good Global Summit held in Geneva, Switzerland. The Summit is the leading action-oriented UN platform to promote AI to advance health, climate, gender, inclusive prosperity, sustainable infrastructure, and other global development priorities.

“As AI use continues to evolve and impact our daily lives, it’s crucial that we ensure its development benefits everyone,” Türk said on the Summit and how it was a great opportunity to work on policies and governance that prevent AI-induced rights abuses.

The Summit was organized by the International Telecommunication Union, the UN specialized agency for information and communication technology, in partnership with 40 UN agencies, including UN Human Rights, and the Swiss government. The Summit aimed to identify practical applications for AI, scale solutions for global impact and accelerate progress towards the UN Sustainable Development Goals.

“Our presence at the AI for Good summit is a testament to the importance of embedding human rights considerations into the fabric of technological innovation,” said Peggy Hicks, Director of the Thematic Engagement, Special Procedures and Right to Development Division at UN Human Rights. “We believe that through multistakeholder efforts, we can achieve a balance where the transformative potential of AI is realized in ways that enhance, rather than undermine, human rights.”[…]

Read more: www.ohchr.org

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