Copyright: Economist Impact – “Seizing the Opportunity: the Future of AI in Latin America”

This report examines the developments in AI in Latin America, with a focus on Argentina, Brazil, Chile, Colombia and Mexico. It looks at AI investment, trends within the region’s industries, as well as policies and challenges. It further explores how AI is impacting the privacy landscape in the region and identifies potential opportunities for businesses, governments and individuals to better understand their roles in safeguarding data.

The proliferation of national strategies highlights the importance of AI to LATAM’s socioeconomic transformation, while policy continuity has been seen to benefit some countries more than others. The debate surrounding the ethical implications of artificial intelligence is still ongoing, and it is important that adequate measures are in place to ensure user privacy when using AI technology. It has become clear that policymakers must strike a balance between driving economic growth through innovation, while also safeguarding citizens’ information from malicious activity.

Investment into tech startups has increased significantly due to its underinvestment historically prior to Covid-19’s shift online, prompting nations “to catch up”.

Major sectors such as Healthtech & Agtech are forecast for growth but remain underinvested compared with Fintech businesses which have proved most attractive due to strong consumer demand.

Key policy issues include the digital infrastructure divide & cultivating local talent; multinational companies have sought regional hubs, but telecom services are still needed along w/ addressing skilled individual drain elsewhere.

Download the report here.

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Astronomy is all about data. The universe is getting bigger and so too is the amount of information we have about it. But some of the biggest challenges of the next generation of astronomy lie in just how we’re going to study all the data we’re collecting.

Copyright by www.weforum.org

1. Planet hunting

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SwissCognitive Guest Blogger: Neil Kitching, geographer and energy specialist from Scotland

Artificial Intelligence is the use of technology to sense their environment, process, problem solve, learn and take action from the analysis of large volumes of data. All AI uses technology built from materials and minerals mined from the ground whilst all AI uses energy to function. More on this later.

AI to monitor the environment

The most obvious environmental use of AI is to deploy sensors to gather information to monitor the environment. For example, sensors in the sewage network can be combined with data from rainfall gauges and weather forecasts (also from AI) to predict sewer overflows in advance. Action can then be taken to divert water flows if possible or to warn residents of an imminent flood risk. The same sensors can monitor the condition of the pipes, detect corrosion and warn of tiny leaks before they grow and burst to enable planned and cost effective maintenance and replacement of buried assets. AI can also use satellite data to analyse and identify changes in land-use such as to spot illegal logging or to monitor changes in soil carbon. This can be combined with payments to ‘offset carbon’ – paying farmers to manage land in a way that protects and enhances soil carbon.

The role of AI in transportation

AI is being used in many transport applications. Intelligent traffic lights, monitoring congestion and optimising routes for passengers and freight will reduce air pollution and carbon emissions. And AI is the backbone of proposed driverless technology. Proponents dream of a future with self-driving electric cars and suggest that this will solve many environmental problems. If we shared such cars and used them constantly then we would need fewer cars. There would be less congestion, less time wasted searching for a vacant car park space and less land taken up by parking spaces. The software could select the most fuel-efficient route and speed. Computer controlled cars with automatic brakes could drive close together reducing wind resistance. But access to self-driving cars is likely to result in an increase in total distance travelled and may increase congestion. For the first time, everyone would have access to a car, people could commute much further and work or sleep during the time spent travelling. In any case, people like to own status goods like cars and might still choose to own a self-driving private car rather than hire one when they need it. Like all technology the outcome depends on what people choose to do – behavioural issues that people who develop technology do not always think through.

Another view of AI in terms of Sustainability

The problem with claims that AI will reduce environmental impact and carbon emissions is that the knock-on consequences are rarely considered. Technology allows us to do more, often more efficiently at a lower price so inevitably demand and consumption increase. Using the clever algorithms used by companies like Amazon, we can now order goods cheaply from anywhere in the world delivered to our door. More stuff, more emissions.

Technology hardware and batteries are made from materials like plastic, silicon, cobalt and lithium. Mining is energy intensive and environmentally destructive and is concentrated in a small number of countries. In the Atacama Desert in Chile, miners inject precious scarce water into underground pools to force the saline water to the surface to concentrate the lithium through evaporation. Some of this water is produced from energy intensive desalination then pumped up mountains to where it is needed. Chile has more than half all known reserves of lithium, whilst other metals such as coltan come from countries prone to conflict, corruption and use of child labour such as the Congo. Without improved efficiency and recycling, our society is in danger of becoming as reliant on these countries as we currently are on oil from the Middle East.

To operate AI requires power, mainly electricity. All connected technology requires electricity to operate the device; to transfer data between the device and servers; and to operate data centres where data is stored. Globally the electricity used to operate this network emits more carbon than aviation. And the volume of data being collected, processed and stored is growing fast. Energy efficiency is improving too, but struggles to keep up with this exponential growth. Obviously the use of renewable electricity is preferable to electricity powered by fossil fuels, but all electricity generation has some form of adverse environmental impact.

New technology, which I cannot claim to understand, has the potential to massively increase electricity consumption. Crypto-currencies require vast amounts of electricity to produce. And any claims made that blockchain will open up ‘sustainable supply chains’ need to be considered alongside the energy required to operate blockchain.

Is AI a force for Sustainable Good or not?

To conclude, AI has many uses that will improve efficiency and reduce carbon emissions. Yet, we also need to work to optimise the design, architecture, storage and energy efficiency of the technology behind AI.

About the Author

Neil Kitching is a geographer and energy specialist from Scotland. He has written his first book, Carbon Choices on the common-sense solutions to our climate and nature crises. He works for a public sector agency promoting the opportunities for business to benefit from low carbon heating and water technologies.

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Mark Barton, Bloomberg anchor, as the event moderator opened the AI Session. Ria Persad, president of European Chamber of Digital Commerce and founder of StatWeather, had the first keynote speech of the day. Ria spoke about the need of business to invest in AI mainly with social and environmental topics as  climate change. She higlighted that companies “need to bring tecnology and AI down to earth in the B2B business”.

Connected to her speech, a panel discussion around ‘World tranformation to digital data on massive scale’ followed through with Mark Minevich and Alan Boehme, Global Innovation Officer from Procter & Gamble, had the future as the center word. Not a better place to talk about the future if is not Davos. The “technomania” mentioned by Sylvain Duranton, Managing Director from Boston Consulting Group, is leading companies and countries to fight for their competitive advantage. Carlos Larraín, Managing Partner at TRES60, affirmed that in Chile started making steps towards the AI research and implementation to be competitive advantaged in the South America scenario. Carlos also highlighted that having the right people will make the difference. Neville Teagarden, Managing Partner at AI Capital, ended the debate with “AI means massive investment and massive risks. But these are manageable risks! We need to take these manageable risks to be able to get into the future”.

Jürgen Schmidhuber, Co-Founder of NNAISENSE, on his keynote speech pointed the potential of artificial intelligence in the future without specifying the concrete application as he said it will become common. “It is going to become more and more accessible for everyone. It is not going to be only for the privileged” stated Jürgen.

Later, Marco Tempest, Creative Technologist at NASA Jet Propulsion Laboratory also known as the ‘Magician’ told the audience a history while he demonstrated with an AI assistante performance the capabilities of the newest technologies.

Ben Pring, Cognizant Vice-President, made strong affirmations about the future of the jobs. In his speech ‘The New Imperative’, Ben adverted to the fact that machines will take some of the jobs. Mainly the repetitives onces where thinking is not needed. But he finalized stating that those changes will occur only to make us better humans dedicated to the important things.

The All Things Connected part was wrapped up with ‘Building impactful AI companies in Europe’ panel. It was agreed that new challenges around AI will bring opportunities for hte companies that are willing to risk. “There are many opportunities. Expertise and data is there – we are just not there yet with technology to be able to combine these” said Nicole Büttner, CEO of Merantix. Merantix founders, Adrian Locher and Rasmus Rothe, together with Nils Regge, Co-Founder of Apollo Ventures, and Thomas Andrae, Managing Partner at Linden Capital, participated at the debate.

Nicolai Wadstrom, BootstrapLabs CEO & Founder, spoke about minding the gap between hype and reality. He boosted the audience with the importance of high performing in designing technology affirming that “We are training computers. They are as good as we make them”.

Hyperconnected Humanity was AI Session last block. Filled with two discussion. One combined with only women talking about the need to trust technology and AI. Dalith Steiger, Co-Founder of SwissCognitive and CognitiveValley, said “We are afraid of something if we don’t know something. This is one of t things we do at SwissCognitive – expectation management: what is possible and what is not. We need to talk about challenges openly. Just because we don’t understand something it should not mean that we don’t discover what it offers to us”. Leila Toplic, Lead for Emerging Technologies NetHope, shared her experience with NGOs. “Tech can help 3rd world countries to have better access to education” and she stated that companies need to be transparent to bring value to their products. Ultimately, Marisa Tschopp, Swiss Ambassador for Woman in AI, rapidly answered that AI will rock because it will help us all.

The last session of the day, ‘When your Lamps, Heaters and Car start talking to each other’. Ezequiel Steiner, Board Member and President of Acronis, shared what Acronis is doing in cybersecurity and how anprotected is everyone. “Companies are vulnerable – but using AI we are able to tackle this problem”. Marco Tempest touched on the ethical part of techonology saying that “big brands will need to live up to their phylosophy. Organisations need to create the right narrative to their own emloyers, customers and peers”. And Nicolai Wadstrom finished saying that a lot has to be discovered yet. 

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Davos is well known for impactful discussion in and outside of the Congress Centre these days, including not only climate change but also digitalization. The SwissCognitive AI Session made a significant impact on Thursday the 23rd of January. In fact, the AI Session brought together more than thirty AI experts to share their knowledge with the Davos community. The event, that took place at the Seehof Hotel, counted with four main topics under the artificial intelligence hat. 

All Things Sensing

Mark Barton, Bloomberg anchor, opened the AI Session as the event moderator. Ria Persad, president of the European Chamber of Digital Commerce and founder of StatWeather, had the first keynote speech of the day. Ria spoke about the need for business investing in AI, mainly applied for social and environmental topics, such as climate change. She highlighted that companies “need to bring technology and AI down to earth in the B2B business”.

Connected to her speech, a panel discussion around ‘World transformation to digital data on a massive scale’ followed through with Mark Minevich and Alan Boehme, Global Innovation Officer from Procter & Gamble. This panel session focus on the future as the main topic. One could guess that Davos is probably one of the best places to discuss the future. The “technomania” mentioned by Sylvain Duranton, Managing Director of Boston Consulting Group, is leading companies and countries to fight for their competitive advantage. Carlos Larraín, Managing Partner at TRES60, affirmed that Chile recently started making steps towards the AI research and its implementation to have a competitive advantage in South America. 

Carlos also highlighted that having the right people will make all the difference. Neville Teagarden, Managing Partner at AI Capital, ended the debate by highlighting that “AI means massive investment and massive risks… but these are manageable risks! We need to take these manageable risks to be able to get into the future”.

All Things Connected

Jürgen Schmidhuber, Co-Founder of NNAISENSE, on his keynote speech pointed the potential of artificial intelligence in the future without specifying the concrete application as he said it will become commonly available everywhere. “AI is going to become more and more accessible to everyone. It is not going to be only for the privileged ones” stated Jürgen. 

Later, Marco Tempest, Creative Technologist at NASA Jet Propulsion Laboratory also known as the ‘Magician’ told the audience a history while he demonstrated some of the AI technology capabilities with the help of an AI assistant in real-time.

Ben Pring, Cognizant Vice-President, made strong affirmations about the future of the jobs. In his speech ‘The New Imperative’, Ben adverted to the fact that machines will take some of the jobs. Mainly the repetitive ones where thinking is not required. However, he finalized stating that those changes will occur only to make us better humans dedicated to the important things.

The All Things Connected part was wrapped up with the ‘Building impactful AI companies in Europe’ panel. It was agreed that new challenges around AI will bring opportunities for the companies that are willing to take some risks. “There are many opportunities. Expertise and data are there – we are just not there yet with technology to be able to combine these” said Nicole Büttner, CEO of Merantix. Merantix founders, Adrian Locher and Rasmus Rothe, together with Nils Regge, Co-Founder of Apollo Ventures, and Thomas Andrae, Managing Partner at Linden Capital, participated at the debate.

All Things Intelligent & Hyperconnected Humanity

Nicolai Wadstrom, BootstrapLabs CEO & Founder, spoke about minding the gap between hype and reality. He boosted the audience engagement by showing the importance of high performing in designing technology. He affirmed that “We are training computers. They are as good as we make them”.

Hyperconnected Humanity was the AI Session on the last block. It was filled with two discussions. One combined with only women talking about the need to trust technology and AI. Dalith Steiger, Co-Founder of SwissCognitive and CognitiveValley, said “Sometimes, humans tend to be afraid of something if they don’t fully understand it. 

This is one of the things we do at SwissCognitive, as we call it ‘expectation management’. This means that we identify what is possible and what is not. We need to talk about challenges openly. Just because we don’t fully understand this technology it does not mean that we don’t discover what it offers to us”. Leila Toplic, Lead for Emerging Technologies at NetHope, a nonprofit technology consortium of 57 global NGOs, shared how the nonprofit sector is using AI to solve societal problems and talked about the importance of responsible innovation. “AI can help us do good better” and she stated that organizations need to innovate responsibly in order to create AI that benefits all. Ultimately, Marisa Tschopp, Swiss Ambassador for Woman in AI, rapidly answered that AI will rock because it will help us all.

The last session of the day, ‘When your Lamps, Heaters and Car start talking to each other’. Ezequiel Steiner, Board Member and President of Acronis, shared what Acronis is doing in cybersecurity and how unprotected it is everyone. “Companies are vulnerable – but using AI we are able to tackle this problem”. Marco Tempest touched on the ethical part of technology saying that “big brands will need to live up to their philosophy. Organizations need to create the right narrative to their own employers, customers and peers”. And Nicolai Wadstrom finished saying that a lot has to be discovered yet.

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He will be presenting his research at the climate conference in Madrid today, and will start a pilot project in Chile in January. Images of burning rainforests in the Amazon region were seared into our memories this summer and raised the question – how much of the forest have we lost? One of the people attempting to answer this question is computer scientist David Dao, a doctoral student from the DS3Lab at the ETH Institute for Computing Platforms.

Dao, who is originally from Germany, is a specialist in machine learning and develops intelligent algorithms that can autonomously analyse satellite and drone images. This helps to reveal where forest coverage is thinning, and to what extent. They can even predict where the rainforest will recede in the near future. The trick is in how the algorithms read the images.

Satellites and drones supply countless images of rainforests – from various altitudes, and in differing resolution and quality. What they have in common is that the regions they depict are not labelled or otherwise identified. Unlike maps, the places don’t bear names, and the forests, rivers and roads have no readily identifiable “signatures”, or “labels”, as a computer scientist would say. This means that computer algorithms are unable to discern what is forest coverage and what isn’t.

“Fish bones” show where forests are shrinking

As Dao explains, the algorithms read sequences in order to recognise which areas are forested and whether these areas are shrinking. These sequences are individual images strung together in chronological succession – much like old film reels or comic strips. So when a new road is built through the rainforest, for instance, numerous smaller roads form off it over time. It is along these roads that the forest coverage is destroyed.

From a bird’s-​eye view, the resulting pattern resembles the skeleton of a fish, with its spine and small bones – thus the moniker “fish bones”. By comparing these chronologically sequential aerial views, algorithms can determine how road systems and forest coverage change over time.

This means that intelligent algorithms don’t need labels to generate an overall image indicating where rainforests are shrinking. They can also predict where the worst deforestation will appear next. This model also applies to deforestation near rivers and around agricultural areas.

Test run in the Chilean rainforest

For the research project, which is called Komorebi, David Dao has attracted partners from the field, including Chile’s forestry authority CONAF (Corporación Nacional Forestal). In January, a pilot project will start in the Valdivian rainforest, on the Pacific coast south of the capital, Santiago. Dao will be testing and tweaking his predictive algorithms in real rainforest conditions. His approach may be able to detect not just overall decline in the rainforest, but also determine which species of trees are most affected. […]

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Artificial Intelligence (AI) is producing new teaching and learning solutions that are currently being tested globally. These solutions require advanced infrastructures and an ecosystem of thriving innovators. How does that affect countries around the world, and especially developing nations? Should AI be a priority to tackle in order to reduce the digital and social divide?

These are some of the questions explored in a Working Paper entitled ‘ Artificial Intelligence in Education: Challenges and Opportunities for Sustainable Development ’ presented by UNESCO and ProFuturo at Mobile Learning Week 2019 . It features cases studies on how AI technology is helping education systems use data to improve educational equity and quality.

Concrete examples from countries such as China, Brazil and South Africa are examined on AI’s contribution to learning outcomes, access to education and teacher support. Case studies from countries including the United Arab Emirates, Bhutan and Chile are presented on how AI is helping with data analytics in education management.

The Paper also explores the curriculum and standards dimension of AI, with examples from the European Union, Singapore and the Republic of Korea on how learners and teachers are preparing for an AI-saturated world.

Beyond the opportunities, the Paper also addresses the challenges and policy implications of introducing AI in education and preparing students for an AI-powered future. The challenges presented revolve around: Developing a comprehensive view of public policy on AI for sustainable development: The complexity of the technological conditions needed to advance in this field require the alignment of multiple factors and institutions. Public policies have to work in partnership at international and national levels to create an ecosystem of AI that serves sustainable development.[…]

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