In this work, we analyze the happiness levels of countries using an unbiased emotion detector, artificial intelligence (AI). To date, researchers proposed many factors that may affect happiness such as wealth, health and safety. Even though these factors all seem relevant, there is no clear consensus between sociologists on how to interpret these, and the models to estimate the cost of these utilities include some assumptions. Researchers in social sciences have been working on determination of the happiness levels in society and exploration of the factors correlated with it through polls and different statistical methods. In our work, by using artificial intelligence, we introduce a different and relatively unbiased approach to this problem. By using AI, we make no assumption about what makes a person happy, and leave the decision to AI to detect the emotions from the faces of people collected from publicly available street footages. We analyzed the happiness levels in eight different cities around the world through available footage on the Internet and found out that there is no statistically significant difference between countries in terms of happiness.
IDSIA（IDSIA研究所）；University of Lugano（卢加诺大学）；IT University of Copenhagen（哥本哈根信息技术大学）
Artificial general intelligence (AGI) refers to research aimed at tackling the full problem of artificial intelligence, that is, create truly intelligent agents. This sets it apart from most AI research which aims at solving relatively narrow domains, such as character recognition, motion planning, or increasing player satisfaction in games. But how do we know when an agent is truly intelligent? A common point of reference in the AGI community is Legg and Hutter's formal definition of universal intelligence, which has the appeal of simplicity and generality but is unfortunately incomputable. G…
Arison School of Business, Interdisciplinary Center (IDC)（阿里森商学院，跨学科中心（IDC））
Focusing on Business AI, this article introduces the AIQ quadrant that enables us to measure AI for business applications in a relative comparative manner, i.e. to judge that software A has more or less intelligence than software B. Recognizing that the goal of Business software is to maximize value in terms of business results, the dimensions of the quadrant are the key factors that determine the business value of AI software: Level of Output Quality (Smartness) and Level of Automation. The use of the quadrant is illustrated by several software solutions to support the real life business chal…
University of Illinois at Chicago（伊利诺伊大学芝加哥分校）；MTA-SZTE Research Group on Artificial Intelligence（匈牙利科学院-塞格德大学人工智能研究组）
We administered the Verbal IQ (VIQ) part of the Wechsler Preschool and Primary Scale of Intelligence (WPPSI-III) to the ConceptNet 4 AI system. The test questions (e.g., "Why do we shake hands?") were translated into ConceptNet 4 inputs using a combination of the simple natural language processing tools that come with ConceptNet together with short Python programs that we wrote. The question answering used a version of ConceptNet based on spectral methods. The ConceptNet system scored a WPPSI-III VIQ that is average for a four-year-old child, but below average for 5 to 7 year-olds. Large varia…
Facebook AI Research（Facebook人工智能研究院）；Virginia Tech（弗吉尼亚理工大学）；Microsoft Research（微软研究院）
As machines have become more intelligent, there has been a renewed interest in methods for measuring their intelligence. A common approach is to propose tasks for which a human excels, but one which machines find difficult. However, an ideal task should also be easy to evaluate and not be easily gameable. We begin with a case study exploring the recently popular task of image captioning and its limitations as a task for measuring machine intelligence. An alternative and more promising task is Visual Question Answering that tests a machine's ability to reason about language and vision. We descr…
Veracity is an essential key in research and development of innovative products. Live Emotion analysis and verification nullify deceit made to complainers on live chat, corroborate messages of both ends in messaging apps and promote an honest conversation between users. The main concept behind this emotion artificial intelligent verifier is to license or decline message accountability by comparing variegated emotions of chat app users recognized through facial expressions and text prediction. In this paper, a proposed emotion intelligent live detector acts as an honest arbiter who distributes …
Comparing model performances on benchmark datasets is an integral part of measuring and driving progress in artificial intelligence. A model's performance on a benchmark dataset is commonly assessed based on a single or a small set of performance metrics. While this enables quick comparisons, it may entail the risk of inadequately reflecting model performance if the metric does not sufficiently cover all performance characteristics. It is unknown to what extent this might impact benchmarking efforts. To address this question, we analysed the current landscape of performance metrics based on da…
Universitat Pompeu Fabra（庞培法布拉大学）；Joint Research Centre, European Commission（欧盟委员会联合研究中心）
The lack of diversity of the Artificial Intelligence (AI) field is nowadays a concern, and several initiatives such as funding schemes and mentoring programs have been designed to overcome it. However, there is no indication on how these initiatives actually impact AI diversity in the short and long term. This work studies the concept of diversity in this particular context and proposes a small set of diversity indicators (i.e. indexes) of AI scientific events. These indicators are designed to quantify the diversity of the AI field and monitor its evolution. We consider diversity in terms of g…
George Mason University（乔治梅森大学）；Virginia Polytechnic Institute and State University（弗吉尼亚理工学院暨州立大学）；Brigham and Women’s Hospital, Harvard Medical School（哈佛医学院布莱根妇女医院）
The quality of service in healthcare is constantly challenged by outlier events such as pandemics (i.e. Covid-19) and natural disasters (such as hurricanes and earthquakes). In most cases, such events lead to critical uncertainties in decision making, as well as in multiple medical and economic aspects at a hospital. External (geographic) or internal factors (medical and managerial), lead to shifts in planning and budgeting, but most importantly, reduces confidence in conventional processes. In some cases, support from other hospitals proves necessary, which exacerbates the planning aspect. Th…
There is a significant lack of unified approaches to building generally intelligent machines. The majority of current artificial intelligence research operates within a very narrow field of focus, frequently without considering the importance of the 'big picture'. In this document, we seek to describe and unify principles that guide the basis of our development of general artificial intelligence. These principles revolve around the idea that intelligence is a tool for searching for general solutions to problems. We define intelligence as the ability to acquire skills that narrow this search, d…
Universidade Federal do Rio Grande do Sul（南里奥格兰德联邦大学）
Recently, the use of sound measures and metrics in Artificial Intelligence has become the subject of interest of academia, government, and industry. Efforts towards measuring different phenomena have gained traction in the AI community, as illustrated by the publication of several influential field reports and policy documents. These metrics are designed to help decision takers to inform themselves about the fast-moving and impacting influences of key advances in Artificial Intelligence in general and Machine Learning in particular. In this paper we propose to use such newfound capabilities of…
Atkinson School of Management, Willamette University（威拉米特大学阿特金森管理学院）；Project Regeneration（再生项目）
Scientists and philosophers have debated whether humans can trust advanced artificial intelligence (AI) agents to respect humanity's best interests. Yet what about the reverse? Will advanced AI agents trust humans? Gauging an AI agent's trust in humans is challenging because--absent costs for dishonesty--such agents might respond falsely about their trust in humans. Here we present a method for incentivizing machine decisions without altering an AI agent's underlying algorithms or goal orientation. In two separate experiments, we then employ this method in hundreds of trust games between an AI…
Multi objective (MO) optimization is an emerging field which is increasingly being implemented in many industries globally. In this work, the MO optimization of the extraction process of bioactive compounds from the Gardenia Jasminoides Ellis fruit was solved. Three swarm-based algorithms have been applied in conjunction with normal-boundary intersection (NBI) method to solve this MO problem. The gravitational search algorithm (GSA) and the particle swarm optimization (PSO) technique were implemented in this work. In addition, a novel Hopfield-enhanced particle swarm optimization was developed…
One of the most important aims of the fields of robotics, artificial intelligence and artificial life is the design and construction of systems and machines as versatile and as reliable as living organisms at performing high level human-like tasks. But how are we to evaluate artificial systems if we are not certain how to measure these capacities in living systems, let alone how to define life or intelligence? Here I survey a concrete metric towards measuring abstract properties of natural and artificial systems, such as the ability to react to the environment and to control one's own behaviou…
This article aims to provide a theoretical account and corresponding paradigm for analysing how explainable artificial intelligence (XAI) influences people's behaviour and cognition. It uses insights from research on behaviour change. Two notable frameworks for thinking about behaviour change techniques are nudges - aimed at influencing behaviour - and boosts - aimed at fostering capability. It proposes that local and concept-based explanations are more adjacent to nudges, while global and counterfactual explanations are more adjacent to boosts. It outlines a method for measuring XAI influence…
In this position paper, I argue that standardized tests for elementary science such as SAT or Regents tests are not very good benchmarks for measuring the progress of artificial intelligence systems in understanding basic science. The primary problem is that these tests are designed to test aspects of knowledge and ability that are challenging for people; the aspects that are challenging for AI systems are very different. In particular, standardized tests do not test knowledge that is obvious for people; none of this knowledge can be assumed in AI systems. Individual standardized tests also ha…
Icelandic Institute for Intelligent Machines（冰岛智能机器研究所）；Reykjavik University（雷克雅未克大学）；The Swiss AI Lab IDSIA（瑞士人工智能实验室IDSIA）
The concept of "task" is at the core of artificial intelligence (AI): Tasks are used for training and evaluating AI systems, which are built in order to perform and automatize tasks we deem useful. In other fields of engineering theoretical foundations allow thorough evaluation of designs by methodical manipulation of well understood parameters with a known role and importance; this allows an aeronautics engineer, for instance, to systematically assess the effects of wind speed on an airplane's performance and stability. No framework exists in AI that allows this kind of methodical manipulatio…
Seoul National University（首尔大学）；AI Institute (AIIS), Seoul National University（首尔大学人工智能研究院）；Dongguk University（东国大学）
We aim to develop an AI agent that can watch video clips and have a conversation with human about the video story. Developing video understanding intelligence is a significantly challenging task, and evaluation methods for adequately measuring and analyzing the progress of AI agent are lacking as well. In this paper, we propose the Video Turing Test to provide effective and practical assessments of video understanding intelligence as well as human-likeness evaluation of AI agents. We define a general format and procedure of the Video Turing Test and present a case study to confirm the effectiv…
Power-law scaling, a central concept in critical phenomena, is found to be useful in deep learning, where optimized test errors on handwritten digit examples converge as a power-law to zero with database size. For rapid decision making with one training epoch, each example is presented only once to the trained network, the power-law exponent increased with the number of hidden layers. For the largest dataset, the obtained test error was estimated to be in the proximity of state-of-the-art algorithms for large epoch numbers. Power-law scaling assists with key challenges found in current artific…
On the Evolution of A.I. and Machine Learning: Towards a Meta-level Measuring and Understanding Impact, Influence, and Leadership at Premier A.I. Conferences
Federal University of Rio Grande do Sul（南里奥格兰德州联邦大学）；Kings College London（伦敦国王学院）；Institute for Infocomm Research, A*STAR（A*STAR资讯通信研究院）；MIT Sloan School of Management（麻省理工学院斯隆管理学院）
Medical University of Vienna（维也纳医科大学）；ITTM S.A.—Information Technology for Translational Medicine（ITTM S.A.——转化医学信息技术公司）；University of Oxford（牛津大学）；Future of Humanity Institute, University of Oxford（牛津大学人类未来研究所）
Benchmarks are crucial to measuring and steering progress in artificial intelligence (AI). However, recent studies raised concerns over the state of AI benchmarking, reporting issues such as benchmark overfitting, benchmark saturation and increasing centralization of benchmark dataset creation. To facilitate monitoring of the health of the AI benchmarking ecosystem, we introduce methodologies for creating condensed maps of the global dynamics of benchmark creation and saturation. We curated data for 3765 benchmarks covering the entire domains of computer vision and natural language processing,…
University of Applied Sciences Esslingen（埃斯林根应用科学大学）；Óbuda University（欧布达大学）；University of Stuttgart（斯图加特大学）
Over the past few years, deep neural networks have shown excellent results in multiple tasks, however, there is still an increasing need to address the problem of interpretability to improve model transparency, performance, and safety. Achieving eXplainable Artificial Intelligence (XAI) by combining neural networks with continuous logic and multi-criteria decision-making tools is one of the most promising ways to approach this problem: by this combination, the black-box nature of neural models can be reduced. The continuous logic-based neural model uses so-called Squashing activation functions…
Cooperative Resilience in Artificial Intelligence Multiagent Systems
Universidad de los Andes（安第斯大学）；Center of Excellence in Analytics and Artificial Intelligence Bancolombia（哥伦比亚银行分析与人工智能卓越中心）；Universidad de Ibagué（伊瓦格大学）
Artificial Intelligence for the Internal Democracy of Political Parties
University of Bologna（博洛尼亚大学）；Yale University（耶鲁大学）；University of Oxford（牛津大学）；Nuffield College, University of Oxford（牛津大学纳菲尔德学院）；Université Libre de Bruxelles（布鲁塞尔自由大学）
Thinking Ahead: Foresight Intelligence in MLLMs and World Model
College of Software, Nankai University, China（南开大学软件学院）；The University of Hong Kong, China（香港大学）；NKIARI, Shenzhen Futian, China（NKIARI，深圳福田，中国）；AAIS & VCIP, Nankai University, China（AAIS与VCIP，南开大学，中国）；A*STAR Institute of Advanced Intelligence and Computing, Singapore（新加坡A*STAR先进智能与计算研究所）
University of Minnesota（明尼苏达大学）；University of Texas Southwestern Medical Center（德克萨斯大学西南医学中心）；Nerves Incorporated（Nerves公司）；Fasikl Incorporated（Fasikl公司）
Objective: The next generation prosthetic hand that moves and feels like a real hand requires a robust neural interconnection between the human minds and machines. Methods: Here we present a neuroprosthetic system to demonstrate that principle by employing an artificial intelligence (AI) agent to translate the amputee's movement intent through a peripheral nerve interface. The AI agent is designed based on the recurrent neural network (RNN) and could simultaneously decode six degree-of-freedom (DOF) from multichannel nerve data in real-time. The decoder's performance is characterized in motor …
