Artificial Intelligence: A European Perspective

We are only at the beginning of a rapid period of transformation of our economy and society due to the convergence of many digital technologies. Artificial Intelligence (AI) is central to this change and offers major opportunities to improve our lives. The recent developments in AI are the result of increased processing power, improvements in algorithms and the exponential growth in the volume and variety of digital data. Many applications of AI have started entering into our every-day lives, from machine translations, to image recognition, and music generation, and are increasingly deployed in industry, government, and commerce. Connected and autonomous vehicles, and AI-supported medical diagnostics are areas of application that will soon be commonplace. There is strong global competition on AI among the US, China, and Europe. The US leads for now but China is catching up fast and aims to lead by 2030. For the EU, it is not so much a question of winning or losing a race but of finding the way of embracing the opportunities offered by AI in a way that is human-centred, ethical, secure, and true to our core values. The EU Member States and the European Commission are developing coordinated national and European strategies, recognising that only together we can succeed. We can build on our areas of strength including excellent research, leadership in some industrial sectors like automotive and robotics, a solid legal and regulatory framework, and very rich cultural diversity also at regional and sub-regional levels. It is generally recognised that AI can flourish only if supported by a robust computing infrastructure and good quality data: • With respect to computing, we identified a window of opportunity for Europe to invest in the emerging new paradigm of computing distributed towards the edges of the network, in addition to centralised facilities. This will support also the future deployment of 5G and the Internet of Things. • With respect to data, we argue in favour of learning from successful Internet companies, opening access to data and developing interactivity with the users rather than just broadcasting data. In this way, we can develop ecosystems of public administrations, firms, and civil society enriching the data to make it fit for AI applications responding to European needs. We should embrace the opportunities afforded by AI but not uncritically. The black box characteristics of most leading AI techniques make them opaque even to specialists. AI systems are currently limited to narrow and well-defined tasks, and their technologies inherit imperfections from their human creators, such as the well-recognised bias effect present in data. We should challenge the shortcomings of AI and work towards strong evaluation strategies, transparent and reliable systems, and good human-AI interactions. Ethical and secure-by-design algorithms are crucial to build trust in this disruptive technology, but we also need a broader engagement of civil society on the values to be embedded in AI and the directions for future development. This social engagement should be part of the effort to strengthen our resilience at all levels from local, to national and European, across institutions, industry and civil society. Developing local ecosystems of skills, computing, data, and applications can foster the engagement of local communities, respond to their needs, harness local creativity and knowledge, and build a human-centred, diverse, and socially driven AI. We still know very little about how AI will impact the way we think, make decisions, relate to each other, and how it will affect our jobs. This uncertainty can be a source of concern but is also a sign of opportunity. The future is not yet written. We can shape it based on our collective vision of what future we would like to have. But we need to act together and act fast.JRC.B.6-Digital Econom

Determining the diagenetic paths of archaeofaunal assemblages and their palaeoecology through artificial intelligence: an application to Oldowan sites from Olduvai Gorge (Tanzania)

The implementation of deep-learning methods to the taphonomic analysis of the microscopic modification of bone-surface modifications exposed to different chemical diagenetic pathways can effectively discriminate between acidic and alkaline soil properties, indirectly reflecting different ecological conditions. Here we use this novel method to assess the sedimentary conditions of two of the oldest Oldowan archaeofaunal records (DS and PTK, Bed I) from Olduvai Gorge Bed I in Tanzania. We show how the results support different diagenetic conditions for both penecontemporaneous sites, which are appropriate for their respective locations on the palaeolandscape to which they belonged. We also show how geochemical analyses of the clay deposit that embedded both sites indicate a similar soil pH divergence. PTK was formed on an alluvial sloping surface affected by rills but draining efficiently, which resulted in alkaline soil conditions, that optimised bone-surface preservation. DS occurred in a more depressed area that underwent intermittent flooding, affecting soil chemistry by creating more acidic conditions. This impacted on bone surfaces by dynamically modifying mark morphology. This deep-learning approach has relevance for the interpretation of the local palaeoecological conditions of both assemblages and their respective depositional loci. The results presented here open a new window to the incremental information gain through the use of artificial intelligence methods in taphonomic and palaeoecological research

A case of hominin scavenging 1.84 million years ago from Olduvai Gorge (Tanzania)

Meat eating is one of the hallmarks of human evolution. It has been linked to the beginning of stone tool use, to physiological changes leading to crucial anatomical transformations defining our genus, and to new socioreproductive and cognitive behaviors. Uncontroversial evidence of meat eating goes back to 2.6 million years ago; however, little is known about the frequency and timing with which early hominins acquired animal resources. Here, we show that the combination of hunting and scavenging documented in some modern human foragers may have a long evolutionary trajectory. Using a new set of artificial intelligence methods for objective identification, we present direct evidence of an episode of hominins scavenging from large felids-probably lions-discovered at Olduvai Gorge (DS site, Bed I). This casts a new perspective on the diversity of hominin carcass acquisition behaviors and survival strategies, and places some early Pleistocene hominins in ecological proximity to African large carnivore guilds

Sabertooth carcass consumption behavior and the dynamics of Pleistocene large carnivoran guilds

Apex predators play an important role in the top-down regulation of ecological communities. Their hunting and feeding behaviors influence, respectively, prey demography and the availability of resources to other consumers. Among the most iconic-and enigmatic-terrestrial predators of the late Cenozoic are the Machairodontinae, a diverse group of big cats whose hypertrophied upper canines have earned them the moniker sabertooths. Many aspects of these animals' paleobiology, especially their prey preferences and carcass consumption behavior, remain unsettled. While skeletal anatomy, dental morphology and wear, and isotopic profiles provide important insights, the most direct way to resolve these issues is through the fossil remains of sabertooth prey. Here, we report on a taphonomic analysis of an early Pleistocene faunal assemblage from Haile 21A (Florida, USA) that preserves feeding damage from the lion-sized sabertooth Xenosmilus hodsonae. Patterns of tooth-marking and bone damage indicate that Xenosmilus fully defleshed the carcasses of their prey and even engaged in some minor bone consumption. This has important implications for Pleistocene carnivoran guild dynamics, including the carcass foraging behavior of the first stone-tool-using hominins

Computer vision supports primary access to meat by early Homo 1.84 million years ago

Human carnivory is atypical among primates. Unlike chimpanzees and bonobos, who are known to hunt smaller monkeys and eat them immediately, human foragers often cooperate to kill large animals and transport them to a safe location to be shared. While it is known that meat became an important part of the hominin diet around 2.6-2 Mya, whether intense cooperation and food sharing developed in conjunction with the regular intake of meat remains unresolved. A widespread assumption is that early hominins acquired animal protein through klepto-parasitism at felid kills. This should be testable by detecting felid-specific bone modifications and tooth marks on carcasses consumed by hominins. Here, deep learning (DL) computer vision was used to identify agency through the analysis of tooth pits and scores on bones recovered from the Early Pleistocene site of DS (Bed I, Olduvai Gorge). We present the first objective evidence of primary access to meat by hominins 1.8 Mya by showing that the most common securely detectable bone-modifying fissipeds at the site were hyenas. The absence of felid modifications in most of the carcasses analyzed indicates that hominins were the primary consumers of most animals accumulated at the site, with hyenas intervening at the post-depositional stage. This underscores the role of hominins as a prominent part of the early Pleistocene African carnivore guild. It also stresses the major (and potentially regular) role that meat played in the diet that configured the emergence of early Homo

Artificial Intelligence at the JRC: 2nd workshop on Artificial Intelligence at the JRC, Ispra 5th July 2019

This document presents the contributions discussed at the second institutional workshop on Artificial Intelligence (AI), organized by the Joint Research Centre (JRC) of the European Commission. This workshop was held on 05th July 2019 at the premises of the JRC in Ispra (Italy), with video-conference to all JRC's sites. The workshop aimed to gather JRC specialists on AI and Big Data and share their experience, identify opportunities for meeting EC demands on AI, and explore synergies among the different JRC's working groups on AI. In comparison with the first event, according to the JRC Director General Vladimír Šuchav, the activities and results presented in this second workshop demonstrated a significant development of AI research and applications by JRC in different policy areas. He suggested to think about replicating the event at the premises of diverse policy DGs in order to present and discuss the clear opportunities created by JRC activities. After the opening speech by the JRC Director General Vladimír Šuchav, the research and innovation presentation were anticipated by two presentations by Alessandro Annoni and Stefano Nativi. The first presentation dealt with the results of one year of AI@JRC and six months of fully operational AI&BD community of practice1. The second presentation reported the results of the AI competences survey at JRC. The research and innovation contributions consisted in flash presentations (5 minutes) covering a wide range of areas. This report is structured according to the diverse domain areas addressed by the presenters. While the first part of the workshop was mainly informative, in the second part we collectively discussed about how to move on and evolve the AI&BD community of practice.JRC.B.6-Digital Econom

Efficacy, safety, and immunogenicity of a booster regimen of Ad26.COV2.S vaccine against COVID-19 (ENSEMBLE2) : results of a randomised, double-blind, placebo-controlled, phase 3 trial

Background Despite the availability of effective vaccines against COVID-19, booster vaccinations are needed to maintain vaccine-induced protection against variant strains and breakthrough infections. This study aimed to investigate the efficacy, safety, and immunogenicity of the Ad26.COV2.S vaccine (Janssen) as primary vaccination plus a booster dose. Methods ENSEMBLE2 is a randomised, double-blind, placebo-controlled, phase 3 trial including crossover vaccination after emergency authorisation of COVID-19 vaccines. Adults aged at least 18 years without previous COVID-19 vaccination at public and private medical practices and hospitals in Belgium, Brazil, Colombia, France, Germany, the Philippines, South Africa, Spain, the UK, and the USA were randomly assigned 1:1 via a computer algorithm to receive intramuscularly administered Ad26.COV2.S as a primary dose plus a booster dose at 2 months or two placebo injections 2 months apart. The primary endpoint was vaccine efficacy against the first occurrence of molecularly confirmed moderate to severe-critical COVID-19 with onset at least 14 days after booster vaccination, which was assessed in participants who received two doses of vaccine or placebo, were negative for SARS-CoV-2 by PCR at baseline and on serology at baseline and day 71, had no major protocol deviations, and were at risk of COVID-19 (ie, had no PCR-positive result or discontinued the study before day 71). Safety was assessed in all participants; reactogenicity, in terms of solicited local and systemic adverse events, was assessed as a secondary endpoint in a safety subset (approximately 6000 randomly selected participants). The trial is registered with ClinicalTrials.gov, NCT04614948, and is ongoing. Findings Enrolment began on Nov 16, 2020, and the primary analysis data cutoff was June 25, 2021. From 34 571 participants screened, the double-blind phase enrolled 31 300 participants, 14 492 of whom received two doses (7484 in the Ad26.COV2.S group and 7008 in the placebo group) and 11 639 of whom were eligible for inclusion in the assessment of the primary endpoint (6024 in the Ad26.COV2.S group and 5615 in the placebo group). The median (IQR) follow-up post-booster vaccination was 36 center dot 0 (15 center dot 0-62 center dot 0) days. Vaccine efficacy was 75 center dot 2% (adjusted 95% CI 54 center dot 6-87 center dot 3) against moderate to severe-critical COVID-19 (14 cases in the Ad26.COV2.S group and 52 cases in the placebo group). Most cases were due to the variants alpha (B.1.1.7) and mu (B.1.621); endpoints for the primary analysis accrued from Nov 16, 2020, to June 25, 2021, before the global dominance of delta (B.1.617.2) or omicron (B.1.1.529). The booster vaccine exhibited an acceptable safety profile. The overall frequencies of solicited local and systemic adverse events (evaluated in the safety subset, n=6067) were higher among vaccine recipients than placebo recipients after the primary and booster doses. The frequency of solicited adverse events in the Ad26.COV2.S group were similar following the primary and booster vaccinations (local adverse events, 1676 [55 center dot 6%] of 3015 vs 896 [57 center dot 5%] of 1559, respectively; systemic adverse events, 1764 [58 center dot 5%] of 3015 vs 821 [52 center dot 7%] of 1559, respectively). Solicited adverse events were transient and mostly grade 1-2 in severity. Interpretation A homologous Ad26.COV2.S booster administered 2 months after primary single-dose vaccination in adults had an acceptable safety profile and was efficacious against moderate to severe-critical COVID-19. Studies assessing efficacy against newer variants and with longer follow-up are needed. Funding Janssen Research & Development. Copyright (c) 2022 The Author(s). Published by Elsevier Ltd