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This special issue interrogates the meaning and impacts of "tech ethics": the embedding of ethics into digital technology research, development, use, and governance. In response to concerns about the social harms associated with digital technologies, many individuals and institutions have articulated the need for a greater emphasis on ethics in digital technology. Yet as more groups embrace the concept of ethics, critical discourses have emerged questioning whose ethics are being centered, whether "ethics" is the appropriate frame for improving technology, and what it means to develop "ethical" technology in practice. This interdisciplinary issue takes up these questions, interrogating the relationships among ethics, technology, and society in action. This special issue engages with the normative and contested notions of ethics itself, how ethics has been integrated with technology across domains, and potential paths forward to support more just and egalitarian technology. Rather than starting from philosophical theories, the authors in this issue orient their articles around the real-world discourses and impacts of tech ethics--i.e., tech ethics in action.
Artificial intelligence (AI) has become a part of everyday conversation and our lives. It is considered as the new electricity that is revolutionizing the world. AI is heavily invested in both industry and academy. However, there is also a lot of hype in the current AI debate. AI based on so-called deep learning has achieved impressive results in many problems, but its limits are already visible. AI has been under research since the 1940s, and the industry has seen many ups and downs due to over-expectations and related disappointments that have followed. The purpose of this book is to give a realistic picture of AI, its history, its potential and limitations. We believe that AI is a helper, not a ruler of humans. We begin by describing what AI is and how it has evolved over the decades. After fundamentals, we explain the importance of massive data for the current mainstream of artificial intelligence. The most common representations for AI, methods, and machine learning are covered. In addition, the main application areas are introduced. Computer vision has been central to the development of AI. The book provides a general introduction to computer vision, and includes an exposure to the results and applications of our own research. Emotions are central to human intelligence, but little use has been made in AI. We present the basics of emotional intelligence and our own research on the topic. We discuss super-intelligence that transcends human understanding, explaining why such achievement seems impossible on the basis of present knowledge,and how AI could be improved. Finally, a summary is made of the current state of AI and what to do in the future. In the appendix, we look at the development of AI education, especially from the perspective of contents at our own university.
IDC estimates that the global artificial intelligence (AI) market is on track to generate $327.5 billion in revenue in 2021, a jump of 16.4% over last year. The research firm anticipates that spending on AI-related hardware, software, and services could increase at an annual rate of 17.5% through 2024 and hit $554 billion in revenue. There are several ways investors can tap into this massive opportunity, as there are a plethora of artificial intelligence stocks out there to choose from. However, Apple (NASDAQ:AAPL), Advanced Micro Devices (NASDAQ:AMD), and Micron Technology (NASDAQ:MU) look like three of the best stocks investors can buy right now to benefit from the massive AI opportunity. Apple gets most of its revenue from selling hardware products such as the iPhone, the iPad, MacBooks, wearables, smart-home devices, and other accessories. These product lines produced nearly 78% of Apple's revenue in the fourth quarter of fiscal 2021, with the services business accounting for the rest.
There is mounting public concern over the influence that AI based systems has in our society. Coalitions in all sectors are acting worldwide to resist hamful applications of AI. From indigenous people addressing the lack of reliable data, to smart city stakeholders, to students protesting the academic relationships with sex trafficker and MIT donor Jeffery Epstein, the questionable ethics and values of those heavily investing in and profiting from AI are under global scrutiny. There are biased, wrongful, and disturbing assumptions embedded in AI algorithms that could get locked in without intervention. Our best human judgment is needed to contain AI's harmful impact. Perhaps one of the greatest contributions of AI will be to make us ultimately understand how important human wisdom truly is in life on earth.
Quanergy Systems, the Sunnyvale, California-based lidar company, said Tuesday it has agreed to merge with special purpose acquisition fund CITIC Capital Acquisition Corp., a Chinese blank-check firm affiliated with the country's largest state-owned investment conglomerate. The deal, which puts an implied valuation on Quanergy at $1.4 billion, is expected to close in the second half of 2021. After closing, the transaction will inject the lidar company with around $278 million in pro forma net cash, including $40 million in private investment in public equity (PIPE) funding. Lidar is an essential component of most autonomous driving systems -- the notable exception being Tesla's stack, which is attempting to develop a pure vision-based system to support its pursuit of automated driving (Tesla vehicles are not autonomous today and have what is considered a Level 2 advanced driver assistance system). Quanergy is a developer of solid state silicon lidar units, which pulses a low-power laser through an optical phased array to measure the distance and shape of objects.
Sometimes, a new technology will change the world forever. 5,000 years ago, a nameless Sumerian started marking clay tablets with a stylus, and invented writing; a little over three centuries ago, the steam engine took its place in our lives; early in the last century, Henry Ford came up with the assembly line. There’s no telling what innovation will prove to be game-changing; but it is possible to narrow the field down. And that brings us to AI. Artificial Intelligence, AI, may just be the next big idea. It’s not quite new – computer scientists and programmers have been working on ‘intelligent machines’ since the 1950s, at least – but the tech is finally maturing, and autonomous computers, capable of collating data and making decisions in real time, are no longer a pipe dream. The implications are staggering. Practical AI makes it possible for machines to learn, and to apply that learning. AI programs underly advanced voice and facial recognition systems and fraud detection programs, applications that depend on pattern recognition. More advanced AI is being applied to the automotive industry, where it is used to monitor automobile systems in real time – and to permit driverless vehicles. And this has not been ignored by Wall Street. Analysts say that plenty of compelling investments can be found within this space. With this in mind, We’ve opened up TipRanks’ database, and pulled three AI stocks that are on the leading edge of the technology. Importantly, all three earn Moderate or Strong Buy consensus ratings from the analyst community, and boast considerable upside potential. TuSimple Holdings (TSP) The first AI stock we’re looking at here, TuSimple Holdings, is deeply involved in the autonomous vehicle industry. The company is working on AI systems that will power self-driving trucks, allowing for greater efficiency and safety in the long-haul trucking industry. TuSimple has developed an advanced autonomous driving system specifically for the needs of the trucking industry; the company’s AI backs a long-range perception system that can spot, recognize, and identify objects as far away as 1,000 meters. In another achievement, TuSimple last summer launched an Autonomous Freight Network, through which the company will address the trucking industry’s challenges. TuSimple’s AI tech will allow the company’s trucks to conduct long-haul freight runs. The AI will monitor sensor systems to keep the truck on the road, and navigate to the destination – in all weather, and even in traffic conditions. To raise capital, TuSimple held its IPO last month, offering 33.75 million shares to the public at $40 per share. Of those shares, 27 million were offered by the company, with an existing shareholder putting 6.75 million shares on the market. TuSimple received the proceeds from the shares it sold directly, totaling over $1.08 billion before expenses. Writing from Canadian investment bank RBC, analyst Joseph Spak notes that TuSimple is highly speculative – but that if it succeeds, the rewards will be enormous. “We understand concerns about vetting the technology, adoption and the path towards revenue and profitability. But if TuSimple succeeds, the equity value is significantly higher. As such, we view TuSimple very much like a venture investment in the public markets or perhaps, a biotech stock. The upside opportunity is massive. Proof points (milestones, orders) along the way should increase the market’s confidence in TuSimple’s mid-term targets and long-term opportunity, thereby increasing its stock price,” Spak explained. In line with his comments, Spak rates TSP an Outperform (i.e. Buy), and sets a $52 price target that suggests an upside of 44% in the next 12 months. (To watch Spak’s track record, click here) Overall, TuSimple personifies everything that risk-loving investors want in the stock market. It uses cutting edge tech; it has staked out a position in a field that is not quite here, but is coming; and it’s an early adopter. While still in early stages of building out its products and AI systems, the stock has attracted 7 analyst reviews – 6 to Buy, and 1 to Hold – giving it a Strong Buy consensus rating. The shares are selling for $36.08, and their $54.70 average price target imply a one-year upside of ~52%. (See TSP stock analysis on TipRanks) Nvidia Corporation (NVDA) Next up, Nvidia, is one of the giants of the silicon microprocessor industry. These are the computer chips that make all of the high tech systems possible. Nvidia was the eighth largest chip maker last year, with more than $16 billion in total sales, up 53% from the year before. Nvidia’s chief connection to AI is through the automotive industry. The company has long sold chips to car makers – automotive business makes up between 5% and 10% of Nvidia’s sales – but the car makers over the past year have been ordering more AI capable systems. Nvidia delivers chips and associated packages that allow an autonomous vehicle’s AI system to build perception, mapping, planning, and monitoring capabilities. Nvidia is working on transferring its automotive AI systems into the data center segment; the monitoring needs of large server stacks are comparable to those of autonomous vehicles, and will benefit from the application of machine learning. Covering NVDA for Baird, 5-star analyst Tristan Gerra rates the stock an Outperform (i.e. Buy) along with an $800 price target, which implies ~45% upside. The bull thesis is based on "Nvidia’s strong near-term positioning in AI data center markets and longer-term opportunities across many accelerated computing applications." (To watch Gerra’s track record, click here) "As Nvidia increasingly moves to platform solutions targeting and enabling all AI markets, while diversifying its architecture offering, the company is poised to over time dominate data center. Omniverse gives us an early glimpse of a virtual 3D world which Nvidia is at the forefront and ultimately yielding to a matrix computing world. More near term, GTC-announced foray into CPUs will expand Nvidia's computing TAM," Gerra opined. Overall, no fewer than 27 analysts have put reviews on NVDA on record, and of those, 24 are to Buy against just 3 to Hold. NVDA shares are selling for $550.34; the average price target of $682.20 implies an upside of 24% from that level. (See Nvidia stock analysis on TipRanks) Upstart Holdings (UPST) We’ll finish in financial tech, where Upstart Holdings has applied AI technology to power a lending platform. Using AI, the company aims to evaluate borrowers to determine actual risk levels and creditworthiness. A clearer understanding of the natural risks of lending money will allow lenders to approve more transactions, give otherwise marginal borrowers greater access to capital, and provide cost savings on both ends. Upstart boasts that its AI analysis platform has helped more than 698,000 customers to acquire loans, and that its model provides for 27% more loan approvals than traditional credit-scoring methods. Upstart’s AI evaluates 1,600 data points, and results in borrowers accessing funds at 16% lower rates than would otherwise be possible. The company has been in business since 2012, and went public on the NASDAQ in December of 2020. The IPO saw the company make 9 million shares made available to the public at $20 each, raising $180 million. In March of this year, Upstart released its first quarterly report as a publicly traded entity. The company reported $86.7 million in total revenues, up 39% from one year earlier. Of that total, $84.4 million was derived from usage fees. For the full year 2020, Upstart saw a 42% yoy increase in revenue, to $233.4 million. Among the bulls is Piper Sandler analyst Arvind Ramnani, who is impressed by both the company’s model, and its forward prospects. "We expect Upstart to expand its market share well beyond its primary product focus of unsecured personal loans, and its recently announced auto loans... Key to Upstart’s AI offering is its a) inherent training data advantage backed by the >1,620 variables aggregated to inform their models; b) AI algorithms that have been extensively tested and refined; c) Over 10.5M discrete repayment events that further validate the data and algorithms. Upstart’s SaaS-based revenue model (only ~1% balance sheet loan exposure) has the ability to deliver upside to our 58% CAGR (2020-2023E), in a massive market ($700B NT; $3.4T LT opportunity),” Ramnani opined. To this end, the analyst rates UPST shares an Overweight (i.e. Buy), and his $143 price target implies an upside of 65%. (To watch Ramnani’s track record, click here) Let’s take a look at how the rest of the Street sees 2021 panning out for UPST. Based on 4 Buys and 2 Holds, the stock has a Moderate Buy consensus rating. The average price target is $123.50 suggesting a 34.5% upside potential from the trading price of $91.82. (See UPST stock analysis on TipRanks) To find good ideas for AI stocks trading at attractive valuations, visit TipRanks’ Best Stocks to Buy, a newly launched tool that unites all of TipRanks’ equity insights. Disclaimer: The opinions expressed in this article are solely those of the featured analysts. The content is intended to be used for informational purposes only. It is very important to do your own analysis before making any investment.
Securing a safe-driving circumstance for connected and autonomous vehicles (CAVs) continues to be a widespread concern despite various sophisticated functions delivered by artificial intelligence for in-vehicle devices. Besides, diverse malicious network attacks become ubiquitous along with the worldwide implementation of the Internet of Vehicles, which exposes a range of reliability and privacy threats for managing data in CAV networks. Combined with another fact that CAVs are now limited in handling intensive computation tasks, it thus renders a pressing demand of designing an efficient assessment system to guarantee autonomous driving safety without compromising data security. To this end, we propose in this article a novel framework of Blockchain-enabled intElligent Safe-driving assessmenT (BEST) to offer a smart and reliable approach for conducting safe driving supervision while protecting vehicular information. Specifically, a promising solution of exploiting a long short-term memory algorithm is first introduced in detail for an intElligent Safe-driving assessmenT (EST) scheme. To further facilitate the EST, we demonstrate how a distributed blockchain obtains adequate efficiency, trustworthiness and resilience with an adopted byzantine fault tolerance-based delegated proof-of-stake consensus mechanism. Moreover, several challenges and discussions regarding the future research of this BEST architecture are presented.
Intel makes processors that act as the main computing brains for PCs and servers. Nomura Instinet chip analyst David Wong initiated coverage on Intel on Tuesday with a Buy rating, predicting long-term sales growth of 8% to 10% annually for the technology giant. "Intel is the world leader in processors for artificial intelligence and autonomous driving," he wrote. "We think that microprocessor growth could well be above overall semiconductor industry growth over the next decade, fueling long-term top-line growth for Intel." The analyst started his price target for Intel at $65, representing 17% upside to the current stock price.
The world never changes quite the way you expect. But at The Verge, we've had a front-row seat while technology has permeated every aspect of our lives over the past decade. Some of the resulting moments -- and gadgets -- arguably defined the decade and the world we live in now. But others we ate up with popcorn in hand, marveling at just how incredibly hard they flopped. This is the decade we learned that crowdfunded gadgets can be utter disasters, even if they don't outright steal your hard-earned cash. It's the decade of wearables, tablets, drones and burning batteries, and of ridiculous valuations for companies that were really good at hiding how little they actually had to offer. Here are 84 things that died hard, often hilariously, to bring us where we are today. Everyone was confused by Google's Nexus Q when it debuted in 2012, including The Verge -- which is probably why the bowling ball of a media streamer crashed and burned before it even came to market.
It has since been updated to include the most relevant information available.] Before we know it, AI will be part of our everyday lives. Market experts say artificial intelligence will lead the next wave of economic growth and productivity for at least the next couple of decades. But many AI stocks have earned a cautious outlook from the Street. We all know the strengths and weaknesses of stocks like Nvidia (NASDAQ:NVDA), Advanced Micro Devices (NASDAQ:AMD) and Tesla (NASDAQ:TSLA), but their challenges are separate from some other heavily AI-influenced stocks.