Category Archives: Artificial Intelligence

The growing use of artificial intelligence (AI) by police forces requires new vigilance on the part of courts and the public about finding the right balance between civil liberties and public safety, warns a professor at the University of California-Davis School of Law.

Law enforcement has been using computers for decades to handle large amounts of investigative information, but new technology such as facial recognition, Shot Spotter, financial anomaly detectio, and automated license plate camera readers, has allowed police to increase the scale and speed of processing information, writes Elizabeth E. Joh, a professor of criminal law and procedure, constitutional law, and policing at the U.C. Davis School of Law

Thatwarrants new scrutiny especially since many communities are unaware of the extent of advanced technology used by their law enforcement agencies, Joh wrote in an essay for Viewpoints, a newsletter published by the Association for Computing Machinery.

For example, the Chicago Police Department uses an algorithm that identifies which city residents may be at especially high risk as perpetrators or victims of gun violence.

Police in Fresno, Ca., piloted an alert system that tells an officer whether the driver the police officer just pulled over to the side of the road poses a threat.

Dozens of other police departments use a program called PredPol, a machine learning algorithm that maps granular 500 x 500-foot sections of the city where crime is more likely to occur, Joh reports.

One danger of the growing reliance on technology is that if the tools malfunction or are used incorrectly, serious consequences can result, according to Joh.

Artificial Intelligence removes human checks where police would traditionally enter a situation using their senses and basic skills to interpret what they are seeing.

Joh gives the example of a bystander reporting abuse.

How would the AI detect truth or lies, she asked?

AI also allows the police to hide their presence in communities, vastly expanding the pool of people and activities the police can watch. Even simple license plate readers identify hundreds of plates a minute.

Moreover, some cameras are connected to the internet, opening up a possibility for hacker activity.

Worse, some [cameras] are leaking sensitive data about vehicles and their drivers and many have weak security protections that make them easily accessible, Tech Crunch writes.

Joh noted that legal rulings already have given a green light to wider law enforcement use of the cellphone location technology.

In Carpenter v. United States, the Supreme Court in 2018 ruled the FBI was able to access the defendants location through cell phone records that showed over 12,000 pings around the time of a robbery, without requiring a warrant.

Even though Carpenters case is not explicitly about AI, it hits notes that are relevant to privacy and information gathering.

The Court was concerned about tools that had extended beyond augmenting the sensory faculties bestowed upon [the police] at birth, Joh explained.

Automated, third-party information-gathering by police challenges traditional notions of privacy, she wrote.

The conventional view is that no matter whether the government has taken one of a thousand snapshots of your face, you have given up your privacy rights, wrote Joh.

The author concludes with a quote from the Carpenter ruling: Unlike the nosy neighbor who keeps an eye on comings and goings, the technology used by the police was ever alert, and [its] memory is nearly infallible.

Courts and civil liberties groups will therefore need to confront a worrying new reality, the paper said.

[The] artificial intelligence tools being adopted by police departments.. are cheap, powerful, ubiquitous, automated and invasive of privacy in ways that are novel and alarming, warned Joh.

See also: CA License Plate Reader Doesnt Protect Privacy

The full paper can be accessed here.

This summary was prepared by Andrea Cipriano, a TCR staff writer.

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Police Use of Artificial Intelligence Poses 'Alarming' Threats to Privacy: Paper - Crime Report

These are the jobs that robots are taking over. Robots take retail. Headlines such as these have become so common, theyre practically accepted as fact. While many are quick to blame advancing technology such as artificial intelligence, the real problem is how that technology is deployed in the workplace along with who stands to benefit from it.

Though tech hubs such as San Francisco, Boston and Seattle routinely grab the limelight, Houston too is on the forefront of an innovation that could drastically change the lives of some workers. Starting last year, a robotics company based in Silicon Valley, Nuro, has been using the suburbs of Houston to test its autonomous grocery delivery service.

In this age of driverless cars, were spending less time celebrating the freedom technology brings and more time worried about what it means for those such as the gig economy workers who deliver groceries who will eventually be replaced by autonomous vehicles.

These concerns are legitimate. Just as urgent is the need to grapple with how we can deploy this new technology to benefit workers. In short, the economic benefits of technology should be broadly shared among all of us.

How technological change is implemented, who benefits and who pays a price, will be based on choices that we make as a society. What scholars are learning, unfortunately, is that high economic inequality is confining the benefits of technological progress and accompanying economic growth primarily to the very rich.

Economic inequality the differences between the top 1 percent and the rest of us has been growing in the United States since the 1980s and stands at its highest point in a century. Houston is not immune: In 2015, the Houston metropolitan area ranked seventh among nearly one thousand metropolitan areas in its share of people who reside in the top 1 percent of incomes nationwide, according to a recent study by the Economic Policy Institute.

Technological progress, while making many workers more productive and adding high-skill jobs to the economy, also reinforces economic and other kinds of inequality, such as by race and gender. Technology has contributed to the rise of independent contractors, franchises and the gig economy. These trends have undermined their bargaining power to obtain wage increases and improved conditions.

Though it might be difficult to predict where technology will take jobs and employment in the decades ahead, we can make policy changes today that address inequality and ensure that workers are treated fairly and can earn their share of the productivity benefits technological advancement provides.

A fundamental step to reducing inequality is to ensure that our economy remains competitive and that the first mover advantage to create new platforms doesnt calcify into monopolies that stifle future innovation and entrepreneurship. Our 21st-century policies must be up to the task of ensuring market competition in the face of new technologies.

We also need to ensure that the gains of growth are shared. We have an easy way to do this: put in place a tax code that does not fossilize wealth into the hands of few. Changes in recent years have mostly benefited the wealthy and corporate interests, not the many. We need a tax code that gives us the capacity to make much-needed investments in our communities and our people that will ensure our economy can be competitive for generations to come. A number of proposals for taxing wealth have been offered; though some go farther than others, any step is a step in the right direction.

And, to directly support the workers who must contend with changing technologies, we need to modernize labor laws and other policies affecting workers to account for the changes taking place in the economy and to reverse actions that have weakened labor unions and worker power. The federal labor standards enacted in the 20th century essentially do not exist for millions of gig workers and others. Those standards for safety, for wages, for working conditions should be updated to meet the needs of todays families by including things like paid leave and extended to all.

In addition, workers voices need to be heard in the workplace. Worker input can lead to greater equity and more efficient production processes. See Harvard Universitys Labor and Worklife Program, which recently issued the Clean Slate for Worker Power, an agenda of policy recommendations that would strengthen the ability of organized labor to rebalance the power between workers and employers.

Luckily Houston has already begun to take action. In 2017, the Mayoral Task Force on Equity produced an in-depth report with a series of recommendations for addressing inequality in Houston. The policies included in Rising Together: A Roadmap to Confront Inequality in Houston ranged from a new jobs program and early childhood education reforms to greater investment in low-income neighborhoods and a more progressive tax system.

Too many conversations about technology and the future of work start from the premise that technology controls us, and not the other way around. If we want to ensure that technology serves all of us and that its benefits are broadly shared then we need to address inequality so that workers are better positioned to weather any challenges the robots might bring.

Boushey is the president and CEO of the Washington Center for Equitable Growth. She will be speaking about her book "Unbound: How Inequality Constricts Our Economy and What We Can Do About It" at Rice University on Wednesday, Feb. 12, at 6:30 p.m. This event is free and open to the public but registration is recommended. She will also be presenting at a Rice Scientia Conference on Work in the 21st Century: Automation, Workers, and Society Feb 13-14.

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Robots and artificial intelligence can benefit workers instead of hurting them if we address inequality today [Opinion] - Houston Chronicle

WASHINGTON, February 13, 2020 Biased artificial intelligence poses obstacles for marginalized communities when trying to access financial services like applying for a mortgage loan, said panelists speaking before the House Committee on Financial Services.

In a statement before the committee on Wednesday, privacy and AI advisor Br A. Williams wrote, Data sets in financial services are used to determine home ownership and mortgage, savings and student loan rates; the outcomes of credit card and loan applications; credit scores and credit worthiness, and insurance policy terms.

In practice, biased AI could mean that black homeowners were confined to specific areas of a city and that their credit worthiness led to higher interest rates, Williams said.

Rayid Ghani, of the Machine Learning Department at Carnegie Mellon Universitys Heinz College of Information Systems and Public Policy, said that it is not enough to create an equitable AI. Rather, there needs to be equity across the entire decision-making process.

Machine bias is not inevitable, nor is it final, concurred Brookings Institution Fellow Makada Henry-Nickie.

This bias though, is not benign. AI has enormous consequences for racial, gender, and sexual minorities, said Henry-Nickie.

University of Pennsylvania Professor Michael Kearns said biased AI is generally not the result of human malfeasance, such as racist or incompetent software developers.

However, Williams argued that if AI is being fed historical data, its already biased.

In order to create an equal AI system, Ghani included steps to an equitable process in the actual construction of AI. Ghani suggested:

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Biased Artificial Intelligence has Sinister Consequences for Marginalized Communities, Argue Panelists - BroadbandBreakfast.com

This report presents the worldwide Artificial Intelligence Robotics market size (value, production and consumption), splits the breakdown (data status 2018 and forecast to 2025), by manufacturers, region, type and application.

This study also analyzes the market status, market share, growth rate, future trends, market drivers, opportunities and challenges, risks and entry barriers, sales channels, distributors and Porters Five Forces Analysis.

The report presents the market competitive landscape and a corresponding detailed analysis of the major vendor/key players in the market.

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Top Companies in the Global Artificial Intelligence Robotics Market:

In global market, the following companies are covered: NVIDIAIntelIBMMicrosoftXilinxSoftbankHanson Robotics

Market Segment by Product TypeService RobotsIndustrial Robots

Market Segment by ApplicationMilitary & DefenseLaw EnforcementHealthcare AssistanceEducation and EntertainmentPersonal Assistance and CaregivingStock ManagementOthers

Key Regions split in this report: breakdown data for each region.United StatesChinaEuropean UnionRest of World (Japan, Korea, India and Southeast Asia)

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The report provides a valuable source of insightful data for business strategists and competitive analysis of Artificial Intelligence Robotics Market. It provides the Artificial Intelligence Robotics industry overview with growth analysis and futuristic cost, revenue and many other aspects. The research analysts provide an elaborate description of the value chain and its distributor analysis. This Tire Artificial Intelligence Robotics study provides comprehensive data which enhances the understanding, scope and application of this report.

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Artificial Intelligence Robotics market recent innovations and major events.

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-In-depth understanding of Artificial Intelligence Robotics market-particular drivers, constraints and major micro markets.

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The report has 150 tables and figures browse the report description and TOC:

Table of Contents

1 Study Coverage

1.1 Artificial Intelligence Robotics Product

1.2 Key Market Segments in This Study

1.3 Key Manufacturers Covered

1.4 Market by Type

1.4.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Type

1.4.2 Hydraulic Dredges

1.4.3 Hopper Dredges

1.4.4 Mechanical Dredges

1.5 Market by Application

1.5.1 Global Artificial Intelligence Robotics Market Size Growth Rate by Application

2 Executive Summary

2.1 Global Artificial Intelligence Robotics Market Size

2.1.1 Global Artificial Intelligence Robotics Revenue 2014-2025

2.1.2 Global Artificial Intelligence Robotics Production 2014-2025

2.2 Artificial Intelligence Robotics Growth Rate (CAGR) 2019-2025

2.3 Analysis of Competitive Landscape

2.3.1 Manufacturers Market Concentration Ratio (CR5 and HHI)

2.3.2 Key Artificial Intelligence Robotics Manufacturers

2.3.2.1 Artificial Intelligence Robotics Manufacturing Base Distribution, Headquarters

2.3.2.2 Manufacturers Artificial Intelligence Robotics Product Offered

2.3.2.3 Date of Manufacturers Enter into Artificial Intelligence Robotics Market

2.4 Key Trends for Artificial Intelligence Robotics Markets & Products

3 Market Size by Manufacturers

3.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.1 Artificial Intelligence Robotics Production by Manufacturers

3.1.2 Artificial Intelligence Robotics Production Market Share by Manufacturers

3.2 Artificial Intelligence Robotics Revenue by Manufacturers

3.2.1 Artificial Intelligence Robotics Revenue by Manufacturers (2019-2025)

3.2.2 Artificial Intelligence Robotics Revenue Share by Manufacturers (2019-2025)

3.3 Artificial Intelligence Robotics Price by Manufacturers

3.4 Mergers & Acquisitions, Expansion Plans

More Information.

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Artificial Intelligence Robotics Market: Drivers, Restraints, Opportunities, and Threats 2019-2029 - Instant Tech News

This has long been a staple of my collection of QTWTAIN Questions To Which The Answer Is No. Originally the question took the form of headlines such as, Will robots replace human journalists? A few years ago, the questions became more insistent as some news organisations experimented with automating sports results or market reporting.

The answer was still always No. Most journalism is a form of conversation. While it is possible to imagine weather reporting or traffic updates being handled by software, writing news stories or comment articles is a form of Turing test that computers are still a long way from passing.

Even so, artificial intelligence is capable of some amazing things. One of the big advances in technology recently has been in voice recognition software. Many journalists, including me, now use a programme called Otter.ai (the ai stands for artificial intelligence), which converts audio recordings into text.

Sharing the full story, not just the headlines

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Editor's Letter: Will artificial intelligence put journalists out of work? - The Independent

Digital agency space150 created a deepfake version of the rapper named Travisbott.

Recent advances in machine learning have allowed musicians like Holly Herndon to use artificial intelligence programs while creating their music. As reported in Adweek, digital agency space150 recently pushed the technology to its limits by creating an entirely AI-generated song with lyrics and melodies modeled after Travis Scotts music.

After two weeks of feeding lyrics into a text generator model, the creative team produced a track titled Jack Park Canny Dope Man by a deepfake version of the rapper named Travisbott. It was released with an unsettling music video:

The track comes complete with Scotts signature its lit and straight up ad-libs and features heavily auto-tuned vocals with nonsensical rhymes:

I aint got the surfers cause I know Im not that hardBut I got all my old bitches mad by the barsThinkin at the Grammys, in the family, I got starsTry to put in the plane, but the blame be on the cars

Ned Lampert, executive creative director at space150, explained to Adweek why the agency created the project, which wasnt designed for any particular client.

We were sort of fascinated with like, What if we tried to make a songlike an actual good songby using AI and basically creative directing AI? he said. And so we chose Travis Scott just because he is just such a unique artist and he has a unique sound and everything sort of has an aesthetic to it, both audibly and visually.

According to Lampert, the bot initially kept generating lyrics about food while it was still learning to mimic the Houston rappers style. There was one line like, I dont want to fuck your party food, he recalled.

Much like Herndon did with her 2019 album, PROTO, the agency used neural network programs to create the melodies and percussion arrangements for the songs instrumental, which falls just short of approximating the feel of Travis' signature sound.

In late 2019, Canadian musician Grimes spoke about AIs growing capacity to create music on the Mindscape podcast. Once theres actual AGI (Artificial General Intelligence), its gonna be so much better at making art than us, she said. Once AI can totally master science and art, which could happen in the next 10 years, probably more like 20 or 30 years.

While Travisbott shows machine learning hasnt surpassed human ability quite yet, AI-generated music continues to improve at a rapid pace.

Check out the full Adweek report here, and read all the lyrics to TravisBotts Jack Park Canny Dope Man on Genius now.

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This Fake Travis Scott Song Created By Artificial Intelligence Sounds Almost Like The Real Thing - Genius

Artificial Intelligence (AI) to be $100 billion sector by 2025

AI startups received $14 billion investment in 2019

AI, an effective tool for Indian Judiciary System : CII Summit and Expo on AI Application & Digi-Tech

Day two ofConfederation of Indian Industrys (CII)Summit and Expo on AI Application & Digi-Tech,kick started with a thought-provoking panel discussion onAI in Public Service.The session highlighted the benefits of AI interventions in Agriculture, Smart Cities, Healthcare, Skilling, Education, Public Utility Services, Judiciary and Governance.

Mr. Sameer Dhanrajani, CEO, AIQRATEsaid that in India we are seeing a great opportunity for AI to support various processes both in the public and private entities. One of the areas where AI can be most effective is in the countrys judicial system. Currently we have 33 million legal cases pending in India. 84% of which has an average pendency of 13 years. AI can be used to deal with all previous cases that we have in our repository by extrapolating it by means of text-mining, multilayer perceptron (MLP) and deep learning. Leaving the legal system to focus on their core job, which is to solve and close cases on an agile basis.

Globally, AI has seen $45 to $58 billion investment during the last year. It is growing at the fastest pace of any exponential technology. The AI segment will be worth over $100 billion by 2025. This gives ample indication of the scale and opportunities in this sector. According to Mr. Dhanrajani, the companies that have adopted AI will take away $1.2 trillion worth of business from their competitors. In 2019 alone AI startups have received $14 billion investment across 600 funding events.

Realizing the importance of AI currently, 28 nations around the world are curating or drafting AI policies and strategies. India is one among them however where the country lags behind is in research. In India we have only 2000 to 2500 research papers submitted every year and China has 10 times more. Out of 34.8 million students coming out of our higher education system in the country only 18% are employed. The job opportunities in the new age will require skills that are not taught in our educational system and this needs to change.

India is uniquely poised to be a global leader in AI, and this is due to the diversity of our population generating a diverse set of data. Attaining a premier position in AI will require convergence of all stakeholders. Towards this, India need to focus on 3 broad areas i.e.Education infusing new age courses and adapting personalized learning powered by AI,Enable create an open innovation platform, a pipeline of AI centric solutions and their adoption andEthics Draft an operating framework within which AI can be developed, Mr. Dhanrajani elaborated.

The panel discussion highlighted the sectors in India where AI can make the most difference:

Governance AI can power several governance initiatives ranging from security threats, RTI, potential fraud and corruption to improving the legal system, curbing human trafficking and tracking of missing persons.

Ms.AparnaGupta,Analytics&DataScienceLeader,OracleCloudSolutionsHub;MrKapilGandhi,VicePresidentStrategyIntelligentAutomation,GenpactDigital;Ms.PadmashreeShagrithaya,VicePresident&HeadAnalytics,DataScienceandVisualization, Capgemini;MrSanjeevKumar,SrDirectorData&Analytics, BakerHughes;MrSatyamoyChatterjeeExecutiveVicePresident AnalytticaDatalabInc also participated in the panel discussion chaired byMr. Sameer Dhanrajani.

With an objective of identifying and showcasing the best Start-up with the most Innovative scale deployment of Artificial Intelligence & Industrial AI in a large corporate environment CII in association withAccenture Ventures held theCII AI Challenge which felicitated the best startups in each of the segment.

AskSidhas been recognized as the Best Start up for Innovative deployment of Artificial Intelligence in large scale corporate environment.

QualitasTechnologieshas been recognized as the Best Start up for Innovative deployment of Industrial AI in large scale corporate environment.

The summit witnessed a live audience poll for the presentation made by the Start-ups and Orbo.aiwas recognized has Best Start up (Audience poll category ).

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Artificial Intelligence to be $100 billion sector by 2025 - CXOToday.com

Radiology is one of the most essential fields in clinical medicine. Experts in this field are specialists in deciphering and diagnosing disease based on various imaging modalities, ranging from ultrasound, magnetic resonance imaging (MRI), computerized tomography (CT), and x-rays. Studies have shown that the use of radiology in clinical practice has exponentially grown over the years: at the Mayo Clinic, between the years 1999 to 2010, use of CT scans increased by 68%, MRI use increased by 85%, and overall use of imaging modalities for diagnostic purposes increased by 75%, all numbers that have likely continued to rise, and indicate the sheer demand and growth of this robust field.

A unique proposal that has become prominent over the last few years to help alleviate this increased demand is the introduction of artificial intelligence (AI) technology into this field. Simply put, the premise of AI as an addition to the practice of radiology is straightforward, and has been envisioned in two main ways: 1) a system that can be programmed with pre-defined criteria and algorithms by expert radiologists, which can then be applied to new, straightforward clinical situations, or 2) deep learning methods, where the AI system relies on complex machine learning and uses neural-type networks to learn patterns via large volumes of data and previous encounters; this can then be used to interpret even the most complicated and abstract images.

Variety of body scans.

However, while much of the theoretical basis for AI in the practice of radiology is extremely exciting, the reality is that the field has not yet fully embraced it. The most significant issue is that the technology simply isnt ready, as many of the existing systems have not yet been matured to compute and manage larger data sets or work in more general practice and patient settings, and thus, are not able to perform as promised.Other issues exist on the ethical aspects of AI. Given the sheer volume of data required to both train and perfect these systems, as well as the immense data collection that these systems will engage in once fully mainstream, key stakeholders are raising fair concerns and the call for strict ethical standards to be put into place, simultaneous to the technological development of these systems.

Furthermore, the legal and regulatory implications of AI in radiology are numerous and complex. There are significant concerns in the data privacy space, as the hosting of large volumes of patient data for deep learning networks will require increased standards for data protection, cybersecurity, and privacy infrastructure. Additionally, given that AI systems will act as an additional diagnostic tool that must be accounted for in the patient encounter, legal frameworks will be required to fully flush out and navigate where liability falls in the case of misdiagnosis or medical negligence. Will this become an issue for the product manufacturer, or will there be a dynamic sharing of the responsibility by multiple parties? This will depend significantly on the amount of autonomy afforded to these systems.

However, radiologists must remain central to the diagnostic process. While AI systems may be able to detect routine medical problems based on pre-defined criteria, there is significant value provided by a trained radiologist that software simply cannot replace. This includes the clinical correlation of images with the physical state of the patient, qualitative assessments of past images with current images to determine progression of disease, and ultimately the most human aspect of medicine, working with other healthcare teams to make collaborative care decisions.

Using a human brain model to interpret MRI scans.

Indeed, there are significant potential benefits to the mass integration of certain AI systems into the practice of radiology, mainly as a means to augment a physicians workflow, especially given increasing radiology demands in clinical medicine. With some reports citing an expected rise in the use of AI in radiology by nearly 16.5% within the next decade, significant complexities remain unaddressed. However, these issues will ultimately need to be resolved in order to achieve a comprehensively capable and ethically mindful AI infrastructure that can become an integral part of clinical radiology.

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Artificial Intelligence Is Not Ready For The Intricacies Of Radiology - Forbes

The role AI plays in your life is a matter of choice (but only to a certain extent).

It doesnt seem too long ago that artificial intelligence (AI) was mostly the stuff of science fiction. Today it seems to be everywhere: in our home appliances, in our cars, in the workplace, even on our wrists.

To some extent, our use of AI is still a matter of personal choice. But because AI is becoming increasing ubiquitous, we need to make a lot of conscious decisions.

Regardless of the choices we make, we need to stay educated on the evolution of this science. A thoughtful primer on this is Rhonda Scharfs bookAlexa Is Stealing Your Job: The Impact of Artificial Intelligence on Your Future.

My conversation with Rhonda provides some good tips what we should know and what we can do.

Rodger Dean Duncan:AI today is similar to the introduction of the desktop computer three decades ago. Many people resisted computers and got left behind. Whats the best argument for AI today?

Rhonda Scharf

Rhonda Scharf:Artificial Intelligence is not going away. When the desktop computer was introduced in the 1980s, many people felt it was a fad, and it would disappear over time.

Hazel, a woman I worked with, was willing to bet her career on it.When the company I worked at insisted we transition to desktops or leave the company, she rolled the dice and called their bluff. She lost. She believed there was no way a company could exist without tried-and-true manual systems and that computers were a big waste of time and money.

We are in precisely that situation again.

If you can write instructions for a task so that someone can follow them, then AI can replicate those actions.

Duncan:So whats the implication?

Scharf:Not only can your company exist without you performing these tasks, it will also (eventually) be more profitable (with fewer errors) because of it.

By refusing to learn about AIand by refusing to adapt and be flexibleyoure rolling the dice that AI will not take over the tasks you currently do. Call yourself Hazel, and youll soon be out of a job.

AI is alive and well in the workplace, only many people dont realize it. Being nave and refusing to acknowledge what is right under your nose is a recipe for disaster. Take a look around at how much AI we already have in our lives. Artificial Intelligence is not going away. Adapt or become unemployed.

Duncan:Most people have grown comfortable with the idea of letting machines replace humans to do monotonous, heavy, repetitive, and dangerous tasks. But the notion of having AI make decisions and predictions about the future often evokes skepticism or even fear. What do you say to people who have such concerns?

Scharf:Movies like2001: A Space Odyessyand its AI character, HAL 9000, have planted the seeds of fear and mass destruction in our minds. We are afraid of what computers can do on their own. AI learns from its experiences and will make decisions on its owncalculated, logical, and statistically accurate decisions.

What AI doesnt do is make emotional decisions. Take AI stock trading as an example. Without any emotions involved, the robo-advisers can determine the optimal price to buy and sell specific stocks. They dont get emotionally tied into one more day and potentially lose profits. AI can evaluate millions of data points and make conclusions instantly that neither humans nor computers can do. As quickly as the market changes, AI changes its course of action based on the data.

Im not about to have AI make life-or-death decisions for me. The same way we now trust machines to handle monotonous, heavy, repetitive, and dangerous tasks, I will rely on AI to do some heavy thinking and bring me logical conclusions, quickly and efficiently.

If you don't want to be left behind, you'd better get educated on AI.

Duncan:What do you tell people who have privacy concerns about AI applications?

Scharf:The privacy concerns are real, but you gave up your privacy when you got your first mobile phone (for some this was as early as 1996). It could track you. Technically, that impacted your privacy 20-plus years ago.

Once the Blackberry was introduced in 1999, followed by the iPhone eight years later, your privacy became severely compromised. Your phone knows where you are, and it knows what youre doing. Even if you keep your Bluetooth off, your device and its apps know a lot about you.

If you wear any technology whatsoever, you are giving up your privacy. According to a 2014 study by GlobalWebIndex, 71% of people ages 16 to 24 want wearable tech. That was over five years ago before we had much wearable technology.

In the same study, 64% of internet users aged 16 to 64 said theyve either already used a piece of wearable tech or were keen to do so in the future.

Fast forward five years, and half of Americans use fitness trackers daily. More than 96% of Americans have a cell phone of some kind.

People may say they have privacy concerns, but when it comes to using technology that improves our lives, we forgo privacy for convenience.

Next: Artificial Intelligence, Privacy, And The Choices You Must Make

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What Role Will (Or Does) Artificial Intelligence Play In Your Life? - Forbes

Artificial intelligence is all the rage, and theres good money to be made in an industry thats still largely emerging from its infancy. But, the problems that AI solves are not easy, and to work in the AI industry you will need a strong and focused set of skills.

Heres the good news: We live in a society where a shocking number of people would rather have a robot boss than a human one. We would rather be led by machines.

This means that most of us are accepting of the idea of artificial intelligence, or AI.

In many sectors, machines have already taken over monotonous jobs. Manufacturing is a prime example. Auto and aerospace manufacturers use machines heavily in their assembly lines. In fact, machines completely transformed the way that our cars are built.

Artificial intelligence isnt just a fad. Its here to stay.

And, that means the industry will need a skilled workforce to build, test and deploy more and more artificial brains around the world. Get in early and youll stand to make a lot of money.

Not to mention help change the world.

If you are interested in a career in artificial intelligence, then youre in the right place.

Artificial intelligence attempts to mimic (and surpass) the power of the human brain using nothing but machines. Machine learning is another common term in AI.

The primary goals of artificial intelligence are:

Artificial intelligence attempts to build machines that think and reason rather than operate in a relatively confined space with pre-built routines, procedures and outcomes. Smart AI systems recognize patterns and remember past events and learn from them, making each subsequent decision smarter, logical and more organic.

AI is a giant paradigm shift in modern computing and requires a deeply scientific and logical approach to design computer systems that think and learn. In other words, build robots that arent just robots.

And believe it or not, AI capabilities are all over the place.

A few examples of artificial intelligence systems include speech recognition (available on many cell phones and smart home devices), email spam blockers, plagiarism checkers, language translation services (like Google Translate) and the auto-pilot system on airplanes.

Companies like Google, Microsoft, Apple, Amazon, Facebook, Accenture, Boeing and so many others are hiring for artificial intelligence roles. AI salaries are typically higher than average because good AI talent can be hard to find.

Artificial intelligence is everywhere in society, and the industry is growing rapidly in 2020. Here is exactly what you need to know to pursue a career in AI.

Artificial intelligence is highly scientific. After all, mimicking the human brain using machines is a very tough problem to solve, much less master. The skills that you will need to pursue AI as a career are varied, but all of them require a great deal of education, training and focus.

That said, there is a wide variety of career types available in AI and machine learning, and they range from higher-level research to low-level programming and implementation.

For example, researchers use their breadth of knowledge in theory and study to reveal new types of systems and capabilities. Researchers hypothesize new or different ways for machines to think and test their research for real-world feasibility.

Algorithm developers take AI research and transform that research into repeatable processes through mathematical formulas that can be implemented using hardware and software.

Software developers and computer scientists use those algorithms to write sophisticated pieces of software that analyze, interpret and make decisions.

Hardware technicians build pieces of equipment (like robots) to interact with the world. Robots use its internal software to move and operate.

Most careers in artificial intelligence require coursework and experience in a variety of math and science-related topics like:

Want a career in AI? Then read. A lot.

Read papers and case studies. Experiment with technologies like Map-Reduce, PHP, MySQL, Postgres and Big Data, especially if you are targeting a computer science-related career in AI. Expose yourself to as many technologies as you can.

Pro tip: Browse through AI job opportunities. Read the job descriptions and especially the requirements to get a feel for specific qualifications that you need for that job.

For example, some might need experience in low-level programming languages like Python or MatLab. Others, especially in the healthcare industry, need expertise in data services like Spark and Blockchain.

Regardless of the type of job that youre after in artificial intelligence, there is no better way to figure out the exact skills you need than to read job requisitions and stay as up-to-date in the industry as possible.

Use the Job Search tool here on The Ladders to find AI and machine learning jobs.

Though the types of careers in the AI industry are varied, most professionals in AI possess five key skills and capabilities, regardless of their individual roles.

Most AI professionals:

Are highly critical thinkers. They take nothing at face value and are naturally curious. They believe in trial and error and must test and experiment before making a concrete decision.

Like to push the envelope. AI is all about pushing the boundaries. Pegging the capabilities of hardware and software to their max, always looking for more. More ways to improve existing systems. More ideas for inventing new ways to live.

Live naturally-curious lives. Always wanting to know more, artificial intelligence pros want to know how things work. They dont just look. They observe. They dont hear. They listen.

Dont get easily overwhelmed. They understand that artificial intelligence is highly technical, but also realize that venturing into uncharted waters is difficult and mysterious. They enjoy the process rather than getting frustrated by it.

Love math and science. AI is highly technical and its a natural good fit for those who are gifted and interested in hard sciences and mathematics.

Artificial intelligence is not just about replacing the human component of the industry. Its also about making it easier to make decisions based on observable patterns, use logic and reasoning to form conclusions and build pathways to boost efficiency and production.

It is not an easy discipline, but thats also why salaries in the AI industry are much higher than average. It takes the right type of person with the right skill set to excel.

Are you the type of person whos right for a career in AI? If you have many of these skill sets, then you just might be.

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These are the exact skills you need to get a job in artificial intelligence - Ladders