Daily Archives: November 13, 2020

Global Conversational Artificial Intelligence and Voice Cloning Market Report 2020-2025: Next Generation Enterprise Solutions by Use Case,…

Posted: November 13, 2020 at 9:48 pm

DUBLIN--(BUSINESS WIRE)--The "Conversational Artificial Intelligence and Voice Cloning Market: Next Generation Enterprise Solutions by Use Case, Application, and Industry Verticals 2020 - 2025" report has been added to ResearchAndMarkets.com's offering.

This research evaluates the market drivers and uses cases for conversational AI and voice cloning solutions to execute various business functions such as CRM. The report analyzes the core technologies used to build conversational AI and voice cloning solutions along with the potential application areas across industry verticals.

The report assesses the impact of the COVID-19 pandemic on the long-term business prospects for this market. It also provides an analysis of leading company strategies, capabilities, and offerings. Forecasts include technologies, solutions, services, applications, tools, and platforms from 2020 to 2025. It also provides forecasts by deployment type, business type (enterprise, SMB, government), industry vertical, and specific applications.

Traditional peer-to-peer communication systems consisting of emails, phone calls, text messages, and face to face meetings have hugely been disrupted with the widespread adoption of next-generation platforms such as social media, messaging apps, and voice-based assistants. This has triggered a major paradigm shift in customer behavior to prefer these alternative communications platforms, providing omnichannel experience regardless of devices. Not surprisingly, younger people are at the tip of the spear of the adoption curve for text but also voice, video, and image sharing.

For additional market segments, a shift occurs in terms of customers' business engagement expectations when they realize they may engage over their favorite chat platform using text, voice, and video communications. Conversational AI plays a profound role here, automatically communicating with customers as if a real human being, but in actuality an authentically human-sounding, AI-powered bot.

Pandemic mitigation is expected to add a significant growth factor to the conversational AI and voice cloning market as businesses seek to automate operations and enhance worker safety as well as support governmental rules and regulations. As the social distancing, remote work and operation, and massive digitization continue to grow, businesses will be more reliant on providing remote services to customers.

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Report Benefits:

Key Topics Covered:

1.0 Executive Summary

1.1 Overview

1.2 Research Objectives

1.3 Select Findings

2.0 Introduction

2.1 Conversational AI

2.1.1 What is Conversational AI

2.1.2 Conversational AI Architecture

2.1.3 Core Challenges

2.1.4 Core Principles

2.1.5 Technology Component

2.1.6 Conversational AI and Chatbot

2.1.7 Automatic Speech Recognition

2.1.8 Growth Drivers

2.2 Voice Cloning

2.2.1 What is Voice Cloning

2.2.2 Voice Cloning Architecture

2.2.3 AI Voice Cloning

2.2.4 Voice Anti-Spoofing and Fraud Detection

2.2.5 Core Challenges

2.2.6 Growth Drivers

2.3 Building Conversational AI and Voice Cloning Solutions

2.4 AI-Enabled Personalization

2.5 Enterprise and Customer Benefits

2.6 Artificial General Intelligence

2.7 Artificial Super Intelligence

2.8 Market Drivers and Challenges

2.9 Value Chain

2.9.1 AI Companies

2.9.2 Software/Platform Companies

2.9.3 Analytics Providers

2.9.4 IoT Companies

2.9.5 Connectivity Providers

2.9.6 Enterprises and End Users

2.10 Regulatory Implications

2.10.1 NHMRC

2.10.2 ADA Accessibility Compliance

2.10.3 The Polish Civil Code

2.10.4 GDPR

2.10.5 HIPAA

2.10.6 PCI DSS

2.10.7 FINRA

2.10.8 SOC 2

2.10.9 MiFID II

2.10.10 CCPA

2.11 COVID -19 Impact

3.0 Technology and Application Analysis

3.1 Conversational AI and Voice Cloning Technology

3.1.1 Machine Learning and Deep Learning

3.1.2 Natural Language Processing

3.1.3 Automatic Speech Recognition

3.1.4 Computer Vision

3.2 Conversational AI and Voice Cloning Application

3.2.1 Chatbots

3.2.2 Intelligent Voice Assistants (IVA) System

3.2.3 Accessibility/ Messaging Application

3.2.4 Digital Games

3.2.5 Interactive Learning Application

3.3 Conversational AI and Voice Cloning Functions

3.3.1 Customer Support

3.3.2 Personal Assistant

3.3.3 Branding and Advertising

3.3.4 Customer Engagement and Retention

3.3.5 Employee Engagement and Onboarding

3.3.6 Data Privacy and Compliance

3.3.7 Campaign Analysis and Data Aggregation

3.4 Conversational AI and Voice Cloning Use Cases

3.4.1 Healthcare and Life Science

3.4.2 Education

3.4.3 Telecom, IT, and Internet

3.4.4 Bank and Financial Institution

3.4.5 Travel and Hospitality/Tourism

3.4.6 Media and Entertainment

3.4.7 Energy and Utilities

3.4.8 Government and Defense

3.4.9 Retail and E-commerce

3.4.10 Manufacturing

3.4.11 Automotive

3.5 Cloud Deployment and Enterprise AI Adoption

3.6 Software Platform and Tools

3.7 5G Deployment and Edge Computing

3.8 Smart Workplace and Service Automation

3.9 Public Safety and Governments

3.10 Ethical Implications

3.11 Social Scam, Theft, and Call Fraud

3.12 Augmented Reality and RCS Messaging

3.13 Multilingualism

3.14 M2M Communications

4.0 Company Analysis

4.1 Acapela Group

4.2 Alt Inc.

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Getting the nitty-gritty of artificial intelligence right – BL on Campus

Posted: at 9:48 pm

If you are a non-technical person learning a technical subject or trying to understand a technical field such as Artificial Intelligence (AI), let me share a simple tip that will help you a lot. Dont let the complex-sounding technical terms confuse you. In due course, you will get comfortable with terminologies if you focus on first principles and try to get an intuitive understanding of the concepts.

So, lets start with the basics and some working definitions. Ive noticed the specific phrase artificial intelligence and machine learning and its shorthand AI/ML being used quite often. They even have more than 15 million and 5 million Google search results respectively. Clearly, their usage is quite common.

But lets examine this phrase AI and ML. Such usage of both AI and ML in one single phrase is actually a marketing practice rather than any technical distinction. Artificial Intelligence is a broad field and Machine Learning is one of its branches. You can think of AI as the superset and ML as its subset. You wont say chai and masala chai when serving a single cup of tea or sell cars and red cars. But hey, using AI and ML makes one sound like an expert and is also good for search engine optimisation.

Next, let me provide working definitions of AI and ML and draw a distinction between them.

Whats intelligence, anyway?

Intelligence is the ability to understand, reason, and generalise. Artificial Intelligence is machines or software having this capability. Intelligence involves the ability for abstraction or generalisation (or in layman terms, common sense). Hence, this kind of AI is also known as Artificial General Intelligence (AGI). In 2020, it may come as a surprise to you but AGI is not on the table at all. We are nowhere close to AGI nor is it clear whether we will ever achieve AGI. Machines with malice, emotions or consciousness, presuppose AGI and are limited to science fiction and movies.

What we instead have is artificial narrow intelligence. Narrow intelligence is a machines ability to perform a single task very well. Examples of such tasks include deciphering handwriting, identifying images, and recognising spoken text. Early approaches, since the 1950s, to master such tasks involved codifying human expertise as rules for computers to follow. It wasnt possible to codify all rules and such rules-based expert systems worked well only in some limited scenarios.

Machine learning, a pattern recognition tool

A different approach is machine learning, where such rules are not explicitly programmed by humans, but the software is fed with large amounts of data to identify patterns and arrive at decision rules. Machine learning is where the software learns the examples it has been provided with and the learning refers the software becoming better with experience (with more data). In other words, machine learning is a great pattern recognition tool.

There are different types of machine learning methods which draw upon mathematics, probability, statistics and computer science for detecting these patterns. One particular set of machine learning techniques, popularly called deep learning, made rapid strides in recent years (and we will discuss deep learning in later columns) and is behind several modern machine learning applications.

These days when you see headlines such as AI solves X, AI-powered software or AI-enabled solution or my favourite AI/ML, it almost always refers to machine learning. Let me make two things clear. First, we made spectacular advances in machine learning in the last ten years. Second, it may not be AGI, but machine learning has a wide variety of uses for consumers, businesses, and governments.

When to use AI/ML

So, what are the takeaways from our discussion of AGI vs ML as you try to utilise ML in your organisation or business?

Machine learning is simply a pattern recognition powerhouse. It seems intelligent but does not have what we consider common sense. To use the example of an AI-powered TV camera which mistook the football referees bald head for the football and focused there instead of the actual match play, it was an amusing illustration of a mismatched pattern. No serious damage and everyone actually got a good chuckle out of this.

But in some situations, the mistakes are costly, even fatal. Take the case of a self-driving car being tested in Arizona in 2018. The algorithm knew to identify pedestrians and cyclists. But the data it was fed did not include a person pushing their cycle and walking alongside it. Arguably, a human driver would not have had a difficulty recognising the pedestrian. The algorithms failure to recognise the scenario contributed to an accident resulting in the pedestrians death.

As a manager who is looking to leverage AI, you should have a good grasp of the nature and scope of machine intelligence, its narrow scope of application, and be able to draw the boundaries beyond which AI will break down. Based on these, you can decide when to rely on AI and when not to. Good managers are expected to make decisions with imperfect data or limited data. AI cant do that!

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Getting the nitty-gritty of artificial intelligence right - BL on Campus

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IBM and AMD will work together on security, artificial intelligence – MarketWatch

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International Business Machines Corp. IBM, +2.05% and Advanced Micro Devices Inc. AMD, -0.50% announced Wednesday morning that they have entered a multi-year agreement focused on enhancing their security and artificial-intelligence offerings. "The joint development agreement will expand this vision by building upon open-source software, open standards, and open system architectures to drive Confidential Computing in hybrid cloud environments and support a broad range of accelerators across high-performance computing (HPC), and enterprise critical capabilities such as virtualization and encryption," the companies said in a release. Confidential Computing is a technology that allows for the encryption of data used to run virtual machines and it helps protect sensitive information. "Confidential Computing for hybrid cloud unlocks new potential for enterprise adoption of hybrid cloud computing, especially in regulated industries such as finance, healthcare and insurance," the companies said in their release. IBM shares are up 0.3% in premarket trading Wednesday, while AMD shares are up 1.4%. IBM shares have lost 12% so far this year as AMD's have risen 70%. The S&P 500 SPX, +1.36% is up 10% in that span, and the Dow Jones Industrial Average DJIA, +1.37%, of which IBM is a component, is up 3%.

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IBM and AMD will work together on security, artificial intelligence - MarketWatch

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Laetitia Cailleteau: Accelerating the Future of Artificial Intelligence with Disruptive Innovation – Analytics Insight

Posted: at 9:47 pm

Accenture is a global professional services company with leading capabilities in digital, cloud and security. They are known for delivering unmatched experience and specialized skills across more than 40 industries, through their Strategy and Consulting, Interactive, Technology and Operations servicesall powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Their 506,000 people deliver on the promise of technology and human ingenuity every day, and serve clients in more than 120 countries. Accenture embrace the power of change to create value and shared success for our clients, people, shareholders, partners and communities.

Laetitia Cailleteau is the Managing Director, UKI Emerging Technology and Global Lead for Conversational AI for Accenture.She is also Accenture Technologys lead for Data & AI in Europe driving innovation, sales, and delivery for multiple industries and clients. She has more than 20 years of experience in the consulting industry, has authored several academic publications, and holds patents in the conversational AI domain. She founded the Liquid Studio in London, an applied innovation lab, where her team offers flagship capabilities within AI and cognitive processes, as well as offering expertise in augmented and virtual reality, Internet of Things, Cloud, Blockchain and Security, amongst other essential technology solutions, while practicing a user-centered approach. She is also a reserve member of the Artificial Intelligence High-Level Group at the European Commission.

During her early 30s, Laetitia found it challenging to juggle the responsibilities of client travel and being a new mother when she landed in the UK, in the middle of what was then the biggest recession in history.

For Laetitia, it was a roller-coaster of new emotions, insecurity and cultural adaptation. It demanded a drive and energy to keep her work and priorities relevant and impactful, and it was finding this balance that helped her center herself. Laetitia realized the importance of the support network which helped bring her new perspective from being a workaholic with not many responsibilities outside work, to being a working mother who needed to cater to so many things and reinvent herself. This support network concept had not struck her as essential before, but it quickly became a matter of survival.

The importance of time became very obvious for her, and so did choosing where to spend it. It was then that she started to engage with WomenInTech in Accenture and charities like riseUp and the Cherie Blair Foundation to help younger individuals from deprived backgrounds and fellow women find their own ways. These were mutually beneficial relationships, helping Laetitia as much as it helped them.

When Laetitia was promoted to Managing Director (MD) just before the birth of her third child, it opened up a number of new doors and presented the perfect opportunity for Laetitia to discover her capabilities through new responsibilities. I landed the perfect job I was asked to create our applied innovation capabilities in the UK. Even better I had a completely blank sheet of paper to start from, says Laetitia.

From there, things quickly gained traction the impact of her teams passion, skills and the technology they managed started to be recognized in both the UK market and on a global scale. Laetitia reminisces, This was when I started to pile-on second hats to my absolute delight, juggling many dimensions of this ever-growing space of Data & AI. She asserts that the breadth of people, clients, problems, and solutions she was interacting with daily helped further fuel her passion for her work.

Laetitia cites that keeping an eye out on the horizon and spotting market opportunities are integral to a leader with a visionary mindset. That skill, coupled with strong communication can enable leaders to demonstrate perseverance, acclimatize to changes, and challenges. They should be able to inspire people, and demonstrate the right cultural and community leadership.

Laetitia shares that the inspiration behind Accentures products usually comes from a mix of things colliding and forming an idea this can be a conversation with people or through conferences, TED talks, news, client challenges, internal targets and thought leadership played against a basis of knowledge of what seems possible or could possibly be. This is where the importance of a diverse team plays in. In addition to the above, surrounding oneself with a diversity of thinking can enable an employee to innovate for a range of target audiences. Upending the hierarchical corporate structure in an organizational group, breaking siloes, and promoting equal opportunities for younger colleagues to lead within the organization also goes a long way. This action dramatically speeds up the flow of ideas and the pace of innovation, and helps define if the ideas are worth pursuing.

Accenture is now a part of a very disruptive tech world. The company can digitize a whole new range of activities that were not possible before. These new technologies blur the boundaries of industries, enabling new levels of collaboration and creating new products and services, only dreamt of before.

Laetitia upholds the notion that the role of a leader in the digital age is to inspire and democratize this knowledge and ensure all employees are on board, while being attentive to the benefits and responsibilities shared across every team and every person within the business.

Laetitia confirms that the 4th industrial revolution has formally kick-started. Companies are aiming to switch towards more human-centered services from industry siloes.Disruptive technologies like AI, machine learning, and big data enable organizations to work smarter and focus on the more rewarding aspects of work and boost productivity.

Hopefully equating to less work and longer weekend for most of us! says Laetitia humorously.

That being said, Laetitia forsees a new world that will be much more inclusive and balanced. She feels that our current mental model of the various phases of life university, work, retirement is somewhat outdated and needs to synch-up with modern life.

Laetitia advises budding leaders to, first and foremost, elevate their individual work in the market and public sphere, get perspectives, take it all in and be relentless with things they believe in. She further encourages to listen, adapt, and not be afraid of getting knocked down, as long as you get back up! According to her, one must chase their dreams and go after things one is passionate about.

Laetitia also affirms that there will be female leaders cheerleading young minds on the way to the top and asks that one must also make sure to lend a hand to pull others up too.

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Artificial Intelligence in mining – are we there yet? – Mining Review

Posted: at 9:47 pm

While Artificial Intelligence (AI) is a much touted technology in mining, it would seem that the sector is yet to fully embrace this advance technology.

Why is this and how can we insure that AI can be beneficial to mining in Africa. GERARD PETER reports.

According to Prof. FrederickCawood, Director of Wits Mining Institute at the University of the Witwatersrand, it will take a policy change to ensure that it can benefit mining in Africa.

Cawood was a panellist on a recent Mining Review Africa webinar titled Mining 2025: A 5-year vision for AI in mining. Cawood was joined on the panel by Eric Croeser, MD for Africa at AccentureIndustry X and Jean-Jacques Verhaeghe, programme managerfor real-time information management systems at Mandela Mining Precinct.

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The webinar focused on understanding AI, its benefits and how to incorporate it into operations.

When asked whether Africa was ready for the implementation of AI, Cawood said that the starting point is policy innovation. The big issue for Africa is poverty.

AI is something that has to be incorporated into the continents mining vision. Because of the perceived threat to job losses, one has to find a balance between the introduction of technology and the poverty reality of the continent. You cant avoid AI; its coming.

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The secret is policy innovation and adopting technology with minimal disruption to the workplace without increasing the cost of business, and also without increasing the cost of consumer goods at the end of the line.

Since AI is a relatively new concept in the mining industry, the sector is yet to fully understand what it truly means and how to incorporate it. Verhaeghe stated that the definition of AI is very broad.

At its highest level, AI is part of digital transformation. It simply boils down to the fact that a machine has the cognitive abilities that we normally associate with humans such as sensing things, learning, reasoning and problem solving.

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The fact is that AI seems so attractive to everyone is because it can do things quicker and better than what a human would typically be able to do, he explained.

Veraeghe further added that the COVID-19 pandemic has accelerated the implementation of AI but at the same time, it is hard to determine just where the industry is when it comes to adopting this technology.

There are varying scales of the adoption of AI in our mines. There are pockets of excellence but its so disparate in terms of where people and companies are at with it. At this point in time most companies are probably just experimenting with the concept, he explains.

He further stated that there seems to be a lack of a cohesive vision across the industry. As such, what is needed is a digitalisation journey that is mapped out and very clearly and deliberately and intentionally drawn up at board level.

Man and machine collaboration

Addressing the subject of the current state of AI in mining and where it will be by 2025, Veraeghe explained that when looking at for any forward projection, we need to distinguish between the normal trends that we see in the economy and the structural shifts.

There are two structural shifts that affected the mining industry. Those are big shifts that require deep innovation and deep thinking. One is the issue of decarbonisation and the other is how technology is affecting the mining workforce; more specifically how it leads to a new world of mining where machines and human beings need to collaborate in the workplace he stated.

Veraeghe stated that AI enables novel production methods where machines do the hard work and humans can use sensors to do observations. Of course, this affects how we collaborate in the workplace and it also effects roles and functions of people in the workplace.

Furthermore, we still have a lot to do in order to get to zero harm as an industry and artificial intelligence can be the next step in working towards this zero harm.

He further added that by 2025, AI will be visible in most work processes along the entire mining value chain. However, he cautioned that governments would have to put policies and laws will have to protect the human workforce.

Meanwhile, Croeser stated that a lot of the AI technology that is implemented in mining has been tested in other industries such as oil and gas.

If you just think about a continuous process, like oil and gas where you when you start from an exploration perspective. So essentially, we have looked at the processes within that industry and then start applying them to a mining process. So we currently delivering programs with our clients.

He further pointed to the fact that recent research shows that there is R28 billion of value in artificial intelligence in mining.

People stand in the way of value. So you need to take the people along. I believe that AI is only way to a fundamental step change in terms of how we run mines from an optimisation, safety and environmental sustainability perspective, he concluded.

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China faces the challenge of keeping its Big Tech in check just like the U.S. does – CNBC

Posted: at 9:46 pm

Jack Ma, CEO of Chinese e-commerce giant Alibaba, speaks during his visit at the Vivatech startups and innovation fair, in Paris on May 16, 2019.

Philippe Lopez | AFP | Getty Images

GUANGZHOU, China China's technology giants are firmly in the crosshairs of the country's regulators who are trying to figure out how to create a set of antitrust rules that can keep these firms in check.

Experts say Beijing will need to ensure that its drive for new regulations balances its push to become a global technological leader.

Like in the U.S., China's tech sector has expanded via a largely unencumbered path. In some areas, regulators have already stepped in and are now stepping up those efforts.

"Like Washington, Beijing has a love-hate relationship with its tech champions," Kendra Schaefer, a partner at Trivium China consultancy which has offices in Beijing and London, told CNBC.

"On the one hand, these companies represent China's successful modernization and growing global competitiveness.On the other hand, Beijing has long struggled with how to fit big tech into the socialist market economy."

Earlier this week, Chinas bureau for regulating monopolies released draft rules that define, for the first time, what constitutes anti-competitive behavior.

The draft regulation by the StateAdministration for Market Regulation covers areas including pricing, payment methods, and use of data to target shoppers. It's the most wide-sweeping attempt to regulate what Beijing sees as monopolistic behavior by the country's tech giants that have grown significantly in the last few years.

The agency is seeking public feedback on the draft rules until Nov. 30.

In China, the services offered by the top tech companies are essential for daily living.

For example, Tencent's WeChat messaging app is used by over a billion people per month. And it's not just a messaging app users can pay for items via WeChat Pay, book flights and trains and shop online, without leaving the app. Tencent is also strong in the gaming sector.

Meanwhile, Ant Group's Alipay is also used by over 700 monthly active users. A third of Ant Group is owned by e-commerce giant Alibaba. But Alibaba is also a cloud computing company as well.

On Wednesday, Chinese tech stocks plunged on news of the draft antitrust rules, given the fact that these internet giants could all fall under the regulation, depending on how it is enforced.

Beijing has looked to tackle aspects of such businesses in the past.

For example, in early 2018, regulators froze the approvals of new video games over fears they contained too much violence and could lead kids to having eye problems. Games need a green light from the regulators to be released and monetized in China. Tencent was particularly hard-hit by that move.

More recently, what would have been Ant Group's world record-setting initial public offering (IPO) in Shanghai and Hong Kong, was suspended. The Shanghai Stock Exchange said Ant had reported "significant issues such as the changes in financial technology regulatory environment." Just days before, theChinese central bank and regulators issued new draft rules for online micro-lending, which could affect Ant Group.

But the new antitrust laws, which are arguably more wide-sweeping, may not be easy to implement.

"I would point out how difficult it has been for regulators in the West, where anti-trust law has a very long history, to figure out how to create laws which will limit their monopoly power," Brian Bandsma, portfolio manager at asset management firm Vontobel Quality Growth, told CNBC.

"Chinese regulators face the same challenge. These businesses are difficult to define and control through traditional legal definitions," Bandsma said.

Yes, the perception appears to be that when Beijing decides to take regulatory action, it will come fast and companies will have to comply.

Late last month, Alibaba founderJack Ma made some comments that appeared critical of China's financial regulator. That was seen as something that stoked regulators into suspending Ant Group's IPO. And some observers say it could also be a factor behind the latest antitrust rules.

"The fact that it is coming on the heels of what Jack Ma said about the financial service regulator, I don't believe is a coincidence," Sam Radwan, CEO of management consultancy Enhance International, told CNBC.

Alibaba, Tencent, Meituan, JD.com and Pinduoduo are all companies that could be affected by the new rules, according to a recent note by Morgan Stanley.

"It will depend on how these guidelines are enforced or whether there is further legislation or regulation in the pipeline," Paul Triolo, head of the geo-technology practice at Eurasia Group, told CNBC by email.

But dealing with regulation is not new for China's technology giants in a market where rules can come into effect unexpectedly and very swiftly.

For example, Tencent has dealt with various regulations on the gaming industry. Chinese fintech company Lufax, which recently listed in New York, was once a peer-to-peer lending giant in China. Buttougher Chinese regulations on the sector forced the company to scale back on that business. In 2019, Lufax exited peer-to-peer lending and has since pivoted to other businesses.

"These companies are also fairly adept at pivoting quickly to incorporate shifting regulatory demands into their business strategies," Trivium China's Schaefer said.

While the U.S. has not yet agreed on what regulation of its large technology firms will look like, the view is that China can move quickly in this area, which may explain the knee-jerk reaction in Chinese technology stocks.

"Yes, the perception appears to be that when Beijing decides to take regulatory action, it will come fast and companies will have to comply," Triolo said. "The latest moves are a kind of warning shot, and like we have seen in Silicon Valley, companies will respond to new rules, and try to preempt others by taking proactive action to address regulators concerns."

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Big tech threw $200m at a ballot measure to hurt gig economy workers. And they won – The Guardian

Posted: at 9:46 pm

One of the darker outcomes of 21st-century work life has been the predatory gig economy. Divorced from healthcare benefits and regular pay, millions of workers are told they are supposed to be lucky to drive passengers around in a car for ever-diminishing returns.

Last week, there was hope that Proposition 22, a ballot measure that allows gig economy companies to continue treating drivers as independent contractors, would be defeated in California, an increasingly progressive state. But voters passed the measure overwhelmingly, thanks to obscene amounts of spending by Uber, Lyft, Seamless and DoorDash. Unleashing more than $200m 10 times the amount of the propositions opponents, like labor unions the coalition of tech giants easily drowned out those fighting for the rights of workers.

The sum is titanic. Uber and its allies left nothing to chance. Reaping billions in investment capital, the companies could easily deploy the cash to crush those advocating on behalf of their workforce.

With Proposition 22s passage, the underclass of these tech giants will remain overworked and underpaid, denied the benefits of full-time employees. They will continue to dwell in precarity, unable to access unemployment insurance, paid family leave or healthcare during a pandemic.

The vote will probably have a nationwide impact, since it rejected the principles outlined in a 2018 state supreme court ruling and enshrined in a 2019 state law that said workers who performed tasks within a companys regular business must be treated as employees. Now gig workers are exempted from these rules and can continue to work independently.

This is a pernicious new era of capitalism, in which companies can brutally exploit their workers without ever turning a profit. Old-world giants, like General Motors, at least needed to make money to survive.

The Uber business model is Trumpian. Storming into cities across the world and openly flouting local regulations, Uber burns up investor cash, winning through sheer ubiquity. Uber loses money every year but devours the market, offering artificially cheap transportation while driving rivals, like taxi drivers, to suicide. There is no way to compete with a company that is allowed to thrive while losing money. Uber can continually discount its rides, confident new capital will arrive to prop it up forever.

In fact, Ubers survival depends on not classifying its drivers as full-time employees. That would make them a conventional company, subject to certain laws of gravity. Workers can be costly; they make demands, after all.

Had Proposition 22 failed, Uber, with its multibillion-dollar valuation, would have been forced to redirect its capital into the pockets of its workers. This, in the long run, would be unacceptable, depriving its wealthy benefactors and executives of their unreality.

In a sane society, a company could not habitually lose money, punish its workers and keep functioning. Uber can.

For much of the 2010s, gig companies coasted on the goodwill of the public. Blissfully unaware of how their goods were rendered so cheaply, most consumers and politicians celebrated the rise of Uber, Lyft and their brethren.

The outcome of this measure should not be treated as a referendum on big tech not with such an absurd spending disparity. Give a labor union $200m to counter propaganda, and a vote total could be flipped. The outcome does, however, serve as a warning to the left that these rapacious companies will do anything and everything to protect their unnatural advantage in the marketplace.

Uber and its ilk treat workers as expendable assets. Having won in California, they will seek devastating victories elsewhere. It will be up to other states, even Congress, to somehow bring these companies to heel. This is the fight that must be joined.

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Big tech threw $200m at a ballot measure to hurt gig economy workers. And they won - The Guardian

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Here’s how Biden will work with Big Tech – CBS News

Posted: at 9:46 pm

Over the last four years, some of America's most prominent technology companies have found themselves squarely in the crosshairs of President Donald Trump. Now industry bellwethers such as Amazon, Apple and Facebook are weighing what kind of reception they can expect from President-elect Joe Biden.

Soon after taking office, Mr. Biden will face a raft of major tech-related challenges, including whether to tighten regulations on social media players, beefing up consumer privacy rules, updating net neutrality policy and tackling the "digital divide" by providing high-speed internet access to people who lack it.

After determining that tech platforms like Facebook and Twitter were used to manipulate the outcome of the 2016 election, Congress launched a series of investigations aimed at curtailing and transforming the tech industry. Democrats tried to uproot and slow the spread of disinformation on social networks, while Republicans alleged censorship of conservative voices and threatened to break up the largest firms.

During the transition, leaders in the tech industry have expressed both trepidation and optimism about the incoming Biden administration. Many fear Mr. Biden could expand federal oversight and use the Justice Department to pursue more antitrust litigation.

But while Mr. Biden has often criticized the industry, others take comfort in the presence of former Apple, Facebook and Google officials on his tech advisory board. A number of Amazon executives also are listed on Biden agency review teams.

Mr. Biden's political team is also advised by a cadre of tech industry types, including executives with political data company Alloy, formed by LinkedIn founder Reid Hoffman, and Google chairpersonEric Schmidt's firmRebellion Defense. Liberal activists fear Mr. Biden's tight tech ties could mean his administration will take a light touch in overseeing tech.

Watch the video above to learn more about how the new presidential administration's major tech policy challenges.

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Here's how Biden will work with Big Tech - CBS News

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Big Tech Is The New Big Tobacco And Joe Biden Doesn’t Get It – HuffPost

Posted: at 9:46 pm

In 2014, the leading economic mind from Barack Obamas administration left office to become president and partner of the private equity firm Warburg Pincus. The revolving door between Wall Street and Washington was a familiar problem at the time, but the details of Timothy Geithners cashout proved unusually gruesome.

Warburg Pincus owns Mariner Finance, a predatory lender devoted to in the words of a devastating Washington Post expos monetizing poor people.

And there was an unfortunate harmony between Geithners public and private careers. The banks had been in serious trouble in 2009, but as Obamas first and most powerful Treasury secretary, Geithner too often prioritized the short-term interests of the financial sector over the needs of struggling families. His most catastrophic decision was on housing, where he transformed a foreclosure relief program into a slush fund for Wall Street, effectively redistributing money from middle class families to the very rich.

Geithner was not the only policymaker to get big questions wrong, of course. The personnel choices Obama made before he even set foot in the White House did much to sabotage his presidency. Although much about the Great Recession and its lackluster recovery can be laid at the feet of Republican obstruction, it is also true that top Obama administration officials frequently pursued bad economic ideas with gusto, leading to disappointing policy outcomes and political dysfunction.

Even before Obamas historic 2008 win was sealed, a then-obscure Citi executive named Michael Froman was compiling a list of top hiring targets for the incoming administration, placing Geithers name alongside figures who included Rahm Emanuel, Eric Holder and Peter Orzsag, all of whom hailed from a Wall Street-friendly milieu and would advance ideas in office that held back the recovery and damaged the administrations public credibility on economic policy.

Judged against that debacle, the news trickling in from President-elect Joe Bidens transition team is in some respects promising. The public list of policy advisers is not stacked with big bank insiders or private equity magnates. There is, in fact, an excellent panel of thinkers on financial reform featuring some of the best minds available, including Gary Gensler, Mehrsa Baradaran, Amanda Fischer, Andy Green, Simon Johnson and others.

But Biden also appears to be trading one set of villains for another. On advisory panel after advisory panel, veterans of big, bad Silicon Valley predators keep popping up Facebook, Uber, Amazon, AirBnB, Lyft and even Mark Zuckerbergs creepy philanthropy all appear. Biden even found a spot for Amazons international tax avoidance guru Tom Sullivan to advise on State Department policy.

The Big Tech crisis of the Trump era has not been as abrupt as the 2008 meltdown, but it has been going on now for years. If Biden allows Silicon Valley to shape the economy of the future, he will damage his presidency just as surely as Obama did by naming Wall Street insiders to a team trying to weather a Wall Street-generated recession.

There was no organized progressive movement pressuring Obama on personnel back in 2008, and for many Democrats it seemed natural that he would be pulling from Bill Clinton administration alumni who had spent their time striking it rich during President George W. Bushs years. Emanuel joined the administration as Obamas first chief of staff after making millions in private equity. Today he is most famous forcovering up the policemurder of 17-year-old Laquan McDonald while serving as Mayor of Chicago. But in 2009, he helped overrule administration economists calling for a larger economic stimulus package, perhaps the biggest blown-call of the Obamas presidency.

Orzsag, as Office of Management and Budget director, was an even more aggressive deficit hawk, pressing the administration to create a commission to fix the unsustainable national debt burden but without ending the Bush tax cuts. He took a job at Citigroup in 2010.

Holder, when named attorney general by Obama, was making millions of dollars a year representing corporate clients including Swiss banking giant UBS and OxyContin manufacturer Purdue Pharma. As attorney general, he refused to prosecute high-level financial fraud, which helped cement the impression that Obama was letting the rich rig his economic program.

Froman, the man with the magic list, ended up with a post as the U. S. trade representative, where he was responsible for the Trans-Pacific Partnership, an 11-nation pact that liberal interest groups and labor unions almost universally derided, and which ultimately failed embarrassing Obama after dividing the Democratic Party.

There were no backroom conspiracies or bags of cash under the table among these players. But they brought a Wall Street-centric view of the world to the administration, where they relied on Wall Street thinking that just happened to be harmful public policy. They believed the deficit was a big deal when it wasnt. They didnt want to raise taxes on corporations or the rich. And they didnt mind flushing homeowners in the name of saving the banks, which, after all, needed to be saved.

The result was a rhetorically liberal presidency in which inequality escalated, the racial wealth gap expanded and American life expectancy declined for the first time since World War I.

Biden has generally avoided Wall Street whiz kids, and outside his financial reform group, there is a trade policy team stacked with capable, reform-minded experts who understand exactly what went wrong on trade under both Obama and Trump. If this list of advisers is any indication, Biden will not be running a big bank White House.

But the Silicon Valley names are frightening. Many of them are Obama White House alums or long-time Biden aides who joined Big Tech and cashed in back when these firms had reputations that were fishy, but not fully toxic. Longtime Biden confidant and turned bigwig Facebook lawyer Jessica Hertz will be running, of all things, ethics policy for the transition. Cynthia Hogan is returning to Bidens team after a stint as a lobbyist for Apple.

Like any other people, politicians trust their old friends. But when your old friends choose to go rake it in at Facebook, a company that poisons democracy all over the world, or Apple, which very publicly bet its future on a cozy relationship with the Chinese government those friends no longer belong in the White House.

Other Big Tech advisers are Obama White House people who were trusted for their expertise and who Biden no doubt continues to respect. But this is precisely the attitude that got Obama into trouble in 2009 with Clinton administration alumni.

Nor is Biden restricting his Silicon Valley search to Obama alums. According to a Financial Times report, Biden is seriously considering a position for former Google CEO Eric Schmidt. He found a labor policy advisory slot for Seth Harris, the intellectual architect of Californias infamous Prop. 22 which rewrites California law to allow Uber, Lyft and other gig economy firms to deny rights, pay and benefits to their workers.

It is hard to overstate just how out of touch Bidens Silicon Valley romance is with todays intellectual consensus on Big Techs role in society. Google is the subject of a landmark antitrust case from the Department of Justice. Uber is something between a laughingstock and a nightmare, so bad that journalists make lists ranking its worst scandals. There are multiple, highly respected think tanks that exist for the sole purpose of reining in Facebook, Apple, Amazon and Google. Sens. Bernie Sanders (I-Vt.) and Elizabeth Warren (D-Mass.) called to break up Big Tech in their primary campaigns, and evenHillary Clinton thinksZuckerberg is an authoritarian.

Thus far, the Biden transition suggests that the Biden White House will be premised on a world a decade out of date one where Democrats knew that Wall Street was a modern Big Tobacco, but hadnt yet realized that tech companies were, too.

Its hard to fix the economy when you dont know whats wrong with it.

Zach Carter is the author of the New York Times bestseller The Price of Peace: Money, Democracy, and the Life of John Maynard Keynes, named by Publishers Weekly as one of theTen Best Books of the Year. It is available from Random House wherever books are sold.

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Big Tech Is The New Big Tobacco And Joe Biden Doesn't Get It - HuffPost

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Investors are losing patience with Big Tech over its lax policing of harmful internet content – MarketWatch

Posted: at 9:46 pm

Free speech and a free press have long been recognized as hallmarks of a functioning democracy; in fact, both are enshrined in the First Amendment of theU.S. Constitution. That said, its quite unlikely that James Madison and his collaborators foresaw an era in which the widespread dissemination of information factually accurate or otherwise could be achieved on a near-global scale and almost instantaneously. The challenges this reality presents are complex and formidable.

While the internet has often beenheraldedas the great democratizer, offering the potential to spread democratic ideals and expand intellectual enlightenment, more nefarious use cases have emerged. Social media platforms have beenexploitedby political operatives, who have used divisive and misleading content to sow seeds of discord and influence election outcomes. The Cambridge Analyicascandalshowed that illicit data harvesting techniques had been employed to psychologically profile and target social media users with often-incendiary political advertising. Meanwhile, some state authorities haveusedsocial media platforms to engage in mass surveillance, or drastically influence political discourse by restricting, filtering, banning or censoring online networks.

Of course, we cant lay the blame entirely at the feet of social media. Aworking paperby University of Chicago economists recently highlighted the role of traditional media in spreading potentially dangerous misinformation, too: it found that areas with greater exposure to a popular cable news show that had downplayed the threat of the novel coronavirus subsequently experienced a greater number of COVID-19 cases and deaths. Its also clear that news reporters face new challenges in the digital age: a 2018reportfrom the Data & Society Research Institute explored the conundrum that journalists face when confronted with how best to cover bigoted, dehumanizing and manipulative messages circulating online. Amplification of such ideas, even when seeking to debunk or dismiss them, can often fuel their adoption.

Lack of exposure to coherent and trustworthy information can yield chaotic results.

As weve seen in the context of the COVID-19 pandemic, a lack of exposure to coherent and trustworthy information can yield chaotic results. Asurveyof respondents across all 50 U.S. states found that individuals obtaining news from social media are more inclined to believe inaccurate information regarding coronavirus conspiracies, risk factors, death rates, and preventative treatments. This can erode faith in global public health organizations, making it more difficult to contain the disease, and in some cases producingtragic consequences.

Meanwhile, the spread of misinformation surrounding other topics has led toviolence,unrest, and even aresurgenceof previously eradicated infectious diseases. As misinformation goes unchecked, and inflammatory postsdeliberatelypit certain groups against one another, Americans growmore dividedthan ever. Quite aside from making for less cohesive and harmonious societies, such misinformation can actually lead to material harms take, for example, theroleof hateful and misleading social media content in precipitating serious human rights abuses in Myanmar.

Perhaps unsurprisingly, there has been a growing public unease in recent years regarding the spread of misinformation online and its negative effects on society. A Pew Researchsurvey, released earlier this year, revealed that most Americans think social media companies wield excessive power and influence in our political landscape, with around half believing that major technology firms should be subject to greater regulation. While content sharing and social media platforms have come under mounting pressure to tackle the spread of misinformation, and haverespondedwith a series of measures designed to flag or remove inaccurate or hateful posts, thedebatearound their culpability (Are they impartial forums for free speech or content publishers?) continues. This poses a regulatory risk for these firms that doesnt appear to be going away anytime soon.

Investors are expressing growing interest in the ethical and financial implications of harmful online content.

In the absence of an imminent regulatory solution, investors are expressing growing interest in the ethical and financial implications of harmful online content, and which companies may be complicit in its distribution. Recently, the nonprofit Sustainability Accounting Standards Board (SASB), which works with businesses to establish reporting standards around financially material sustainability issues, indicated forthcoming scrutiny of companies content moderation practices. A press releaseannouncedthat in part owing to investor concern, and indicators that content moderation practices can yield significant financial impact it will be evaluating technology companies efforts to manage pernicious user-generated content, political advertisements and other third-party content thats hosted on their platforms.

If you are keen to divert money away from companies that could be doing more to curb misinformation and preserve democracy, there are data points you can turn to. First, you might want to consider a companys known media ethics events, spanning incidents that relate to a breach in editorial or generalmedia ethics, and violations of content restrictions. These ethical breaches can present financially material risks, potentially harming a companys reputation, leading tofines, advertiser/consumer boycotts and legal trouble that canaffectcompanies balance sheets for years to come.

Investors might also evaluate the quality of a firms media ethics program, and corresponding editorial guidelines, which can shed light on a companys commitment to upholding ethical standards during the content creation and dissemination process. Robust measures should place emphasis on contents transparency, fairness, independence, plurality and inclusiveness of viewpointsand should be promoted from the top down. Organizationstendto have fewer ethical lapses when leadership actively adopts ethics programs, and ensures opportunities for education and problem-solving exercises surrounding ethical best practices.

Many companies still have a long way to go when it comes to instituting strong content governance measures, though. A 2017analysisof 74 conventional and social media firms found that just 16% had adequate or strong content governance measures in place, while 61% failed to provide satisfactory disclosures about relevant policies. With a record number of Americans nowexpressingzero confidence in traditional news media, and withdistrustof internet platforms precipitating a public techlash, content governance metrics will have greater financial importance.

By enhancing awareness of media ethics issues, and the steps that companies are taking to address them, we can collectively make more informed decisions about where to invest our time and money. With great power comes great responsibility, and media companies of all kinds have both the powerandthe responsibility to ensure that the content they disseminate or host is fair, accurate, and inclusive. Whats at stake? Potentially, democracy as we know it.

Jay Lipman is cofounder and president of Ethic, which creates personalized ESG portfolios for financial advisors and institutional investors.

More: Social medias U.S. election performance: The good, bad and (sometimes) ugly

Also read: Only a breakup of Facebook and controls on social media can reduce disinformation and lies on the internet

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