AI

• Shortly thereafter, the consensus switched to fears of an imminent nuclear holocaust.
• Similarly, today’s experts warn that an artificial general intelligence (AGI) doomsday is imminent.
• It’s difficult to argue with David Collingridge’s influential thesis that attempting to predict the risks posed by new technologies is a fool’s errand.

• Focusing on the economic risks from AI is not simply about preventing “monopoly,” “self-preferencing,” or “Big Tech dominance”.
• It’s about ensuring that the economic environment facilitating innovation is not incentivising hard-to-predict technological risks as companies “move fast and break things” in a race for profit or market dominance.
• OpenAI is already becoming a dominant player with US$2 billion (£1.6 billion) in annual sales and millions of users.

Degrading quality for higher profit

• The problems fostered by social media, search, and recommendation algorithms was never an engineering issue, but one of financial incentives (of profit growth) not aligning with algorithms’ safe, effective, and equitable deployment.
• For digital platforms, extracting digital rents usually entails degrading the quality of information shown to the user, on the basis of them “owning” access to a mass of customers.
• But over time, a misalignment between the initial promise of them providing user value and the need to expand profit margins as growth slows has driven bad platform behaviour.

Amazon’s advertising

• In our research on Amazon, we found that users still tend to click on the product results at the top of the page, even when they are no longer the best results but instead paid advertising placements.
• For social media platforms, this was addictive content to increase time spent on platform at any cost to user health.
• In the process, profits and profit margins have become concentrated in a few platforms’ hands, making innovation by outside companies harder.
• Amazon’s most recent quarterly disclosures (Q4, 2023), shows year-on-year growth in online sales of 9%, but growth in fees of 20% (third-party seller services) and 27% (advertising sales).
• Algorithms have become market gatekeepers and value allocators, and are now becoming producers and arbiters of knowledge.

Risks posed by the next generation of AI

• But how much greater are the risks for the next generation of AI systems?
• Thankfully, society is not helpless in shaping the economic risks that invariably arise after each new innovation.
• Risks brought about from the economic environment in which innovation occurs are not immutable.
• Market structure is shaped by regulators and a platform’s algorithmic institutions (especially its algorithms which make market-like allocations).
• What role might interoperability and open source play in keeping the AI industry a more competitive and inclusive market?
• Instead, we should try to recalibrate the economic incentives underpinning today’s innovations, away from risky uses of AI technology and towards open, accountable, AI algorithms that support and disperse value equitably.

• Ilan Strauss receives funding from The Omidyar Network through the UCL IIPP research project on algorithmic rents Mariana Mazzucato received funding for this project from the Omidyar Foundation.
• Rufus Rock received funding from the Omidyar Network whilst pursuing the research referenced in this piece.

• In an article published today in Nature, my colleagues and I show that illicit, often out-of-control road building is imperilling forests in Indonesia, Malaysia and Papua New Guinea.
• Once roads are bulldozed into rainforests, illegal loggers, miners, poachers and landgrabbers arrive.
• Once they get access, they can destroy forests, harm native ecosystems and even drive out or kill indigenous peoples.
• All nations have some unmapped or unofficial roads, but the situation is especially bad in biodiversity-rich developing nations, where roads are proliferating at the fastest pace in human history.

Mapping ghost roads

• This workforce then spent some 7,000 hours hand-mapping roads, using fine-scale satellite images from Google Earth.
• For starters, unmapped ghost roads seemed to be nearly everywhere.
• In fact, when comparing our findings to two leading road databases, OpenStreetMap and the Global Roads Inventory Project, we found ghost roads in these regions to be 3 to 6.6 times longer than all mapped roads put together.

• When ghost roads appear, local deforestation soars – usually immediately after the roads are built.
• We found the density of roads was by far the most important predictor of forest loss, outstripping 38 other variables.

Roads and protected areas

• In protected areas, we found only one-third as many roads compared with nearby unprotected lands.
• The bad news is that when people do build roads inside protected areas, it leads to about the same level of forest destruction compared to roads outside them.
• Keeping existing protected areas intact is especially urgent, given more than 3,000 protected areas have already been downsized or degraded globally for new roads, mines and local land-use pressures.

Hidden roads and the human footprint

• To gauge how much impact we’re having, researchers use the human footprint index, which brings together data on human activities such as roads and other infrastructure, land-uses, illumination at night from electrified settlements and so on.
• When ghost roads are included in mapping the human impact on eastern Borneo, areas with “very high” human disturbance double in size, while the areas of “low” disturbance are halved.

Artificial intelligence

• Worse, these roads can be actively encouraged by aggressive infrastructure-expansion schemes — most notably China’s Belt and Road Initiative, now active in more than 150 nations.
• You might think AI could do this better, but that’s not yet true – human eyes can still outperform image-recognition AI software for mapping roads.
• Once we have this information, we can make it public that so authorities, NGOs and researchers involved in forest protection can see what’s happening.

Distinguished Professor Bill Laurance receives funding from the Australian Research Council and other scientific and philanthropic bodies. He is a former Australian Laureate and director of the Centre for Tropical Environmental and Sustainability Science at James Cook University.

• LPKF had forecast Group revenue of between EUR 125 million and EUR 135 million and an EBIT margin of 3–7% for the 2023 financial year.
• These include severance costs and the change in the value of virtual share options issued in 2023.
• The Management Board believes that LPKF has made good progress towards achieving its strategic corporate targets in key areas in the 2023 financial year.
• LPKF expects these costs to amount to 0.5 – 1.5% of revenue in the 2024 financial year.

• Xlife Sciences is pleased to announce a collaboration between its portfolio company, FUSE-AI, and T-Systems Switzerland.
• T-Systems Switzerland, as a subsidiary of T-Systems International GmbH, is considered a system-relevant IT and digitalization partner in the healthcare sector in Switzerland.
• Through this cooperation, T-Systems Switzerland distributes the AI-based solution for prostate analysis from FUSE-AI centrally in Switzerland, thereby enabling the commercialization of «Prostate.Carcinoma.ai» for radiological clinics and practices.
• Xlife Sciences sees this partnership as a significant contribution to continuing its mission to bridge the gap between innovations and the needs of the healthcare market.