Business Analytics Test 1 - Chp 14

AI and Law (applications of AI in field of law)

Areas of interest: • Analyzing legal-related data (e.g., regulatory conflicts) to detect pattern • Providing legal advice to consumers (e.g., see DoNotPay.com). • Document review • Analyzing contracts • Supporting legal research • Predicting results (e.g., likelihood to win) • AI impact on the legal profession.

Jobs and the Nature of Work Will Change

• Many activities done by humans will have the potential to be automated. • Productivity growth from robotics, AI, and machine learning will be tripled compared to pre-2015. • AI will create many new jobs paying high salaries. • Since more than half the world is still offline, the changes will not be too rapid.

Impact on Business

-There is very little doubt that we will see increased commercialization of AI, especially in marketing, financial services, manufacturing, and IT support. -predicted that there will be more proactive processes rather than reactive ones. -There will be more people-machine collaboration and while many jobs will be automated, many new ones will be created. There is going to be more conversational AI due to the increased capabilities of chatbots and personal assistants

Ambient Computing (Intelligence)

- Electronic environment that is sensitive and responsive to people. The technology serves the environment and acts to support the involved people in their tasks. -Potential benefits of ambient computing • Recognize individuals and other "things" and their context at any given time and place. • Integrate into the environment and existing systems. • Anticipate people's desires and needs without asking (e.g., context awareness). • Deliver targeted services based on people's needs. • Be flexible (i.e., can change their actions in response to people's needs or activities). • Be invisible.

Impact on Quality of Life

-A major area where AI intelligent systems have already made a stride is the healthcare field. -According to Editors (2018) smart solutions can improve quality of life indicators by 10 to 30 percent. Among the indicators that they cite are: having longer and healthier lives, reducing greenhouse gas emissions, saving 200,000 lives worldwide over 10 years (thanks to self-driving cars), reducing the commute time for people (fewer traffic problems), increasing the number of jobs (e.g., by new technologies and more productive business environments), and providing better and more affordable housing.

Industrial Restructuring

-A new Industrial Revolution - change this time around significantly more far reaching is that the technology is enabling many cognitive tasks to be done by machines. -Different and far reaching than before: enabling many cognitive tasks to be done by machines -Speed of change is so radical... societal impacts! -The examples are not just in games like Jeopardy! or G O, but also in real life, speech recognition image processing...

Connectivity and Integration

-AI and analytic applications need to be connected to the existing IT systems

Leveraging Intelligent Systems in Business

-According to Catliff 2017 1. Customize the customer experience (e.g., for interactions with customers). 2. Increase customer engagement (e.g., via chatbots). 3. Use intelligent technologies to detect problems and anomalies in data. -Singh (2017a) recommends the following as critical success factors to use intelligent systems: 1. discover 2. predict 3. justify 4. learn from experience.

The AI Utopia's Position - optimistic approach to AI

-Crime fighting in Santa Cruz, California where AI was able to predict where and when crimes will occur. Following the predictions, the police department has been planning its work strategies. The result is a 20 percent reduction in crime. -Prediction of the probability that a song will be a hit -Finding the perfect match for dating in a population of 30,000 -Primary idea: AI will partner and support humans to innovate

Impacts on jobs and work

-Generally agreed that: • Intelligent systems will create many new jobs as automation always has. • There will be a need to retrain many people. • The nature of work will be changed. -Polarization of the labor market (in the future) -Most jobs lost will be in the middle—middle skills (ones with specialized knowledge applied same over and over) are at risk of disappearing -even if AI does not replace workers directly, it will certainly require employees to acquire new skills to keep their jobs.

Privacy Issues

-It is difficult to determine/enforce privacy regulations -Collecting information about individuals - Intelligent technologies aim to provide targeted services and marketing to consumers; they do so by collecting information about these customers. Internet is the enabler of new face of data collection -Virtual personal assistants - Amazon's Echo/Alexa and similar devices listen to what is going on at all times -Mobile user privacy - Tracking through the smartphones - not just the cell-phone providers but potentially many apps on your phone -Privacy in IoT networks - More data are flowing with IoT networks. AI data privacy issues are on the rise, especially when AI deals with consumers' data. -Recent technology issues in privacy and analytics- with the growth of Internet users in general and mobile device users, many companies have started to employ intelligent technologies to develop profiles of users on the basis of their device usage, surfing, and contacts. other issue is in analyzing employee behaviors on the basis of data collected from sensors that employees wear in a badge. -Other privacy issues • Delaware police are using AI dashcams to look for fugitives in passing cars. Photos and videos taken are sent to the clouds and analyzed there by AI algorithms. • Facebook's face recognition systems create concerns regarding privacy protection. • Epicenter offers its employees a microchip implant. It acts like a swipe card, opens doors, buys you food in the company store, and much more. But management can track you too. It is given only to volunteers.

Impact of Intelligent Systems on Organizations

-Knowledge revolution - is taking place very rapidly and affecting every facet of our work and lives. Inherent in this transformation is the impact on organizations, industries, and managers -New organizational units and their management - One change in organizational structure is the possibility of creating an analytics department, a BI department, a data science department, and/or an AI department in which nalytics plays a major role. -Transforming businesses into digital ones and increasing competitive advantage -Using intelligent systems to gain competitive advantage -Using robots Amazon.com enabled the company to reduce cost and control online commerce -Autonomous vehicles will impact the competition in the automotive industry -The impact of computers and intelligent systems can be divided into three general categories: (1) organizational, (2) individual, and (3) societal

Other topics in intelligent systems

-Machine ethics is a part of the ethics of AI that is concerned with the moral behavior of artificially intelligent beings. -Robotics is concerned with the moral behavior of designers, builders, and users of robots. -Microsoft's Tay chatbot was closed due to its inability to understand many irrelevant and offending comments. -Some are afraid that algorithm-based technologies, including AI, may become racists. -Self-driving cars may one day face a decision of whom to save and whom to kill. -Voice technologies enable the identification of callers to AI machines. Good, but also creates privacy concerns -One area in which there are considerable ethical concerns (frequently combined with legal concerns) is the healthcare/medical field.

Security Protection

-Many intelligent applications are managed and updated in the "cloud" and/or connected to the regular Internet. Unfortunately, by adding Internet connection, new vulnerabilities may be created. Hackers use intelligent technologies to identify these vulnerabilities. -the safety of people working near robots needs to be considered. In addition, hacking robots, chatbots, and other intelligent systems are areas that require attention. The safety of robots themselves when they work on the streets is an issue.

Redesign of an Organization Through the Use of Analytics

-People analytics - Data science for studying organizational dynamics, personnel behavior, and redesigning the organization to better achieve its goals -HR for better/faster hiring, and employee management -Creating data (G P S and sensor)-driven, better-functioning project teams and environments - Humanyze claims "... successful leaders indeed have larger networks with which they interact, spend more time interacting with others, and are also physically active"

Ethical issues

-Personal values constitute a major factor in the issue of ethical decision making. -The study of ethical issues is complex because of their multidimensional nature, something may not be illegal, but may not be ethical either -Transparency on what AI does for both vendors and customers is needed in order to stay ethical. This way people can stay honest and adhere to the goals of AI, so it can play a significant role in our life and work.

Intelligent systems may actually add jobs

-PwC - robots will create 7 million new jobs in U K -IBM new deep learning service saves I T jobs -Automation will fill unfilled 50K truck driver jobs -Gartner Inc. predicts that by 2020, AI will create more jobs than it eliminates -New categories of human jobs that have been created by AI -Some believe that there will be a total of increase in jobs due to A I-induced innovations -It was estimated that in 2018 there would be over 490,000 jobs open for data scientists, but only 200,000 scientists will be available. However, in the long run, AI and machine learning may replace most data scientists (Perez, 2017) -Violino (2018) says that most workers see robots as an aid to their jobs

Conclusion: Let's Be Optimistic!

-Replacing many human jobs and reducing wages are [hopefully] exaggerated -Instead, intelligent technologies will clearly contribute to shorter work time for humans.

Top Management and Implementation

-Senior executives need to understand the tactical as well as the strategic opportunities (of AI) -Need to Plan/prepare to 1. Redesign their organization 2. commit to helping shape the future of work 3. Integrate intelligent systems into their workplace.

ET brain project (ALIBABA project)

-The logic is that today and in the near future, we are and will be doing business in the cloud computing environment. Content, knowledge, and data are in the cloud - ETBrain consists of three parts: 1. technologies - include Big Data and analytic processing, neural networks, video recognition analysis, and machine learning. These technologies provide four major capabilities such as cognitive perception, reasoning, real-time decision making, and machine learning 2. capabilities - reasoning and real time decision making, machine learning with perceptual innovation, cognitive perception with multidimensional awareness, and strategic decision making with situational intelligence 3. applications (innovations) - such as e-commerce activities (both business-to-business and business-to-consumers), medical and health care, smart cities, agriculture, travel, finance, and aviation.

Topics related to deployment strategy

-When to start intelligent projects and how to prioritize them. -How to decide whether to do it yourself or outsource. -How to justify investments in intelligent projects. -How to overcome resistance (e.g., fear of job loss). -How to arrange appropriate people-robot teams. -How to determine which decisions to fully automate by AI. -How to protect intelligent systems security and privacy. -How to handle possible loss of jobs and retraining. -How to determine whether you have the needed technology. -How to decide what support top management should provide. -How to integrate the system with business processes. -How to find qualified personnel for building and using intelligent systems.

Who owns private data

-You or the technology creators? -A new car with sensors to collect data and connected to the Internet to disseminate it -New battle between car manufacturers and tech providers (Apple, Google) as to who can access this data -Apps collect data abut the users: Google's Waze, Yelp, Spotify -Privacy issues are considered in many cases as important components of ethics.

Open AI Project

-a non-profit organization -Created by Elon Mask and others to prepare against the unintended action of robotics and AI -Safe artificial general intelligence (AGI) - plan of the project is to build safe AGI and ensure benefits are evenly distributed

The O'Neil Claim of Potential Analytics' Dangers

-argues that models (AI) must satisfy three conditions. 1. they must be transparent - That is, if the model is not understandable, its application can lead to unintended consequences. 2. the model must have clear quantifiable objectives. 3. models must have a self-correcting mechanism and a process in place so that they are audited regularly and new inputs and outputs are constantly being considered.

KPMG's holistic approach to implementation

-from strategy through execution execs will assist companies on each step of implementation. The steps are: • Establishing priority areas for technological innovation. • Developing a strategy and a plan for the employees. • Identify providers and partners for plans' execution. • Establishing a strategy and plans to realize benefits from the digital labor initiatives.

The Largest Opportunity in Business

-intelligent technologies provide the largest opportunity for tech companies since mobile computing. -Tech companies has been the beneficiary of AI -Despite their rivalry, Facebook, Amazon, Google, IBM, and Microsoft partner to advance practices in AI

Privacy

-is the right to be left alone and the right to be free from unreasonable personal intrusions -Related to legal, ethical, and social issues in many countries. It recognized today by federal government and by every state in the US either by statute or by common law -Two rules that applies to interpretation of privacy 1. The right of privacy is not absolute (needs to be balanced against the needs of the society) 2. The public's right to know is superior to the individual's right to privacy

Gartner's Top Strategic Technology Trends for 2018 and 2019

1. AI Foundation and Development - Advanced AI systems that support decision making, some of which are autonomous, and other AI systems are developed in conjunction with analytics and data science. 2. Intelligent Apps and Analytics - Almost all IT systems will include AI in the next few years. 3. Intelligent and Autonomous Things - Utilizing the IoT capabilities, there will be an explosion of autonomous vehicles and a significant increase of other intelligent things (e.g., smart homes and factories where robots are assembling robots). 4. Digital Twin - A digital twin refers to digital representations of real-world objects and systems. This includes mainly IoT systems with 20 billion connected things in two to three years. 5. Empowered Cloud (Cloud to the Edge) - In Edge computing, information collection, processing, and delivery are conducted closer to the sources of the information. 6. Conversational Human-Machine Platforms. These platforms already facilitate natural language interactions, resulting in improved collaboration. These include smart collaborative spaces 7. Immersive Experience - These systems change the manner in which people can see and perceive the world (e.g., augmented reality). 8. Blockchain - Blockchain technologies offer a radical platform for increased security and trust, significantly improving business transactions. 9. Augmented Analytics - Using machine learning enables this technology to focus on transformation of analytics, so it will be better shared and consumed. This will facilitate data preparation management and analysis to improve decision support. 10. Others - These include smart collaboration space, Quantum computing, digital and ethical privacy, and adopting risks and trust.

Some issues related to utopia

1. AI will be so great that people will have a problem of what to do with their free time. If you have not yet seen Disney's Wall-E movie, go and see it. It shows how humans are served by robots. Dennis Hassabis, a strong proponent of Utopia (from Deep Mind, an AI company), believes that AI will one day help people have a better life by understanding what makes humans unique, what the mysteries of the mind are, and how to enjoy creativity. 2. The road to AI Utopia could be rocky, for example, there will be impacts on jobs and work. It will take time to stabilize and adjust work and life of living with robots, chatbots, and other AI applications. 3. One day we will not drive anymore and there may not be human financial advisors; everything will be different, and the changes may be rapid and turbulent and we may even face disasters, as projected by the Dystopia camp.

System Development Implementation Issues

1. Development approach - Business analytic and AI systems require an approach different from that of other IT/computer systems. Specifically, it is necessary to identify and deal with different and frequently large data sources. It is necessary to cleanse and curate these data. If learning is involved, one needs to use machine training. Thus, special methodologies are needed. 2. Learning from data - Many AI and business analytics involve learning. The quality of the input data determines the quality of the applications. Also, the learning mechanism is important. Therefore, data accuracy is critical. In learning, systems must be able to deal with changing environmental conditions. Data should be organized in databases, not in files. 3. No clear view is available of how insights are generated - AI, IoT, and business analytic systems generate insights, conclusions, and recommendations based on the analysis of the data collected. Given that data are frequently collected by sensors and there are different types of them, we may not have a clear view of the insights that are generated.

What Are the Major U.S. High-Tech Companies Doing in the Intelligent Technologies Field?

1. Google - uses NLP in its Google Translate as well as in its search processes. It uses neural networks in its immersed databases (for pattern recognition) and for making decisions on them. In addition, Google uses other machinelearning algorithms for personalization advertising decisions. 2. Apple - is known to secretly be working on several AI projects. The most known is its Siri chatbot, which is embedded in several of its products (e.g., iPhone). In 2016, Apple acquired a machine-learning company, Turi. 3. Facebook - new business unit that identifies important AI developments and incorporates them into Facebook's products. Facebook invested billions of dollars in AI. 4. Microsoft - is very active in all AI technology research. In 2017, it acquired Maluuba, a start-up that specializes in deep learning and NLP. Maluuba excels in reading and comprehending text with near human capabilities in its virtual personal assistant, Cortana. This assistant helps people deal with e-mail and messaging difficulties. The AI will examine the content of messages and any stored documents and advice for what actions to take. 5. IBM - entered robotics as early as 1973. By 1980, it had developed the QS-1; by 1977, it had developed Deep Blue; and by 2014, a mature IBM Watson entered the scene. IBM is also known for its artificial brain project.

Impacts of intelligent systems

1. Impact on organization - comprised of impacts on structure, employees, management & D/M, industries, and competition 2. Work and Jobs - look at jobs to be automated, safe jobs, changes on the nature of work 3. Potential unintended impacts - Dangers of AI and robots, dangers of analytical model, mitigating the dangers

Major steps of implementation

1. Need assessment - Need assessment needs to provide the business case for the intelligent systems, including their major parts. focus is on business case and priority of need 2. Preparations - In this step, it is necessary to examine the organization readiness for analytics and AI. It is necessary to check available resources, employees' attitudes and assess legal privacy and ethics issues 3. System acquisition - Organizations need to decide on in-house or outsourcing approach (make or buy) or on a combination of the two and possibly with partnership with a vendor or another company. 4. System development (and deployment) - certain activities need to be done. These include security, integration with other systems, project management preparation. 5. Impact assessment - check the performance of the systems against plans. Success and failure analysis, impact on people and productivity overall

White-Collar Jobs That Robots Have Already Taken

1. Online marketers - Using NLP, companies are automatically developing marketing ads and e-mails that influence people to buy (robo marketers). These are based on a dialog with potential buyers and on an automatic database search of historical cases. "Who needs an online marketer that may have inferior, biased, or incomplete knowledge?" 2. Financial analysts and advisors - robo advisors are all over the scene. Equipped with the ability to deal with Big Data in real time and conduct predictive analysis in seconds, these programs are liked by investors who pay about one-tenth of what human advisors charge. Furthermore, robo advisors can personalize recommendations. 3. Anesthesiologists, diagnosticians, and surgeons - The medical field seems to be immune from AI. This is not the case. Expert systems for diagnosis have been in place for about 40 years. The FDA has already approved the J&J Sedasys system for delivery of low-level anesthesia in surgeries, such as colonoscopies. IBM's Watson has demonstrated a far more accurate diagnosis in lung disease cases than humans (90% vs. 50%). surgeons already use automated machines in some invasive procedures. 4. Financial and sports reporters - These jobs involve gathering information, interviewing people, answering questions, analyzing the material, and writing reports. The Associated Press (AP) has experimented with AI machines since 2014. Results so far are virtually error and bias free

AI Research Activities in China

1. TENCENT - giant e-commerce company has created a huge AI lab to manage its AI activities. The goal is to improve AI capabilities and support decision making in the following areas: computer vision, NLP, speech recognition, machine learning, and chatbots. AI is already embedded in over 100 Tencent products, including WeChat and QQ. 2. Baidu - started NLP research five years before Google to improve its search engine capabilities. The company is located in the Silicon Valley, Seattle, and Beijing. Baidu has several products. One is Duer OS, a voice assistant that is embedded in more than 100 brands of appliances in several countries. The product is now optimized for smartphones. Baidu is also working on autonomous vehicles. the company promotes facial recognition in the enterprise 3. ALIBABA - The world's largest e-commerce company and the provider of cloud computing and IoT platforms, Alibaba is active in AI projects and is an investor in AI companies, such as in the face recognition giant SenseTime. Alibaba has developed a methodology for conducting AI

The 10 commandments of computer ethics:

1. Thou shalt not use a computer to harm other people. 2. Thou shalt not interfere with other people's computer work. 3. Thou shalt not snoop around in other people's files. 4. Thou shalt not use a computer to steal. 5. Thou shalt not use a computer to bear false witness. 6. Thou shalt not use or copy software for which you have not paid. 7. Thou shalt not use other people's computer resources without authorization. 8. Thou shalt not appropriate other people's intellectual output. 9. Thou shalt not program without thinking about the social consequences of the program you write. 10. Thou shalt not use a computer in ways that do not show consideration and respect.

Impact on AI and Analytics (summary)

1. Today, Narrow AI - Increase capabilities with time, but no match to human intelligence. -possible impacts - Increasingly perform routine tasks, some with human. Provide speed, quality and advice. Cut cost 2. In 20-25 years, Artificial General Intelligence - Autonomous systems all over; limited reasoning capabilities; adopt to changes in the environment; can self-expand tasks; can reason, innovate. -Possible impacts - Autonomous vehicles are all around. Robots assume more tasks. People have more time. Compete with humans 3. In Distant Future, Super AI - As intelligent as human and even more in some cases. Major support to research, innovation and learning -Possible impacts - Can be dangerous if not controlled. Can significantly improve our quality of life

Dealing with the changes of jobs and work - suggestions

1. Use learning and education to facilitate the change. 2. Involve the private sector in enhancing training and retraining. 3. Have governments provide incentives to the private sector so employees can invest in improved human capital. 4. Encourage private and public sectors to create appropriate digital infrastructure. 5. Innovative income and wage schemes need to be developed. 6. Carefully plan the transition to the new work. Deal properly with displaced employees. 7. Properly handle new technology-enabled technologies. 8. Focus on new job creation, particularly digital jobs. 9. Properly capture the productivity increase opportunities.

Ethical Issues of Intelligent Systems

1. What are their impact on jobs (see Section 14.5)? 2. How do machines (i.e., robots) affect our behavior and interactions? 3. How can wealth created by intelligent machines be distributed (e.g., Kaplan, 2016)? 4. How can intelligent applications mistakes be guarded against? For example, how long should training programs in machine learning be? 5. Can intelligent systems be fair and unbiased? How can bias in creation and operation of AI systems be eliminated? 6. How can intelligent applications be keep safe from adversaries? 7. How can systems be protected against unintended consequences (e.g., accidents in robot operations)? For example, Facebook researchers had to shut down an AI system that created its own poor language. 8. How can we stay in control of a complex intelligent system? 9. Should we develop robots' legal rights? How can we define and plan human treatment of intelligent machines? 10. Should we allow a self-governing robot society to exist with ours? 11. To what extent should we influence unintended robots' behavior (or even be able to)? 12. How would we get around the question of smart machine ownership?

SAS Real-Time Decision Manager (RTDM)

1. What does SAS RTDM do? It combines SAS analytics with business logic and contact strategies to deliver enhanced real-time recommendations and decisions to interactive customer channels, such as Web sites, call centers, point of sales (POS) locations, and automated teller machines (ATMs). 2. Why is SAS RTDM important? It helps you make smarter decisions by automating and applying analytics to the decision process during real-time customer interactions. By successfully meeting each customer's specific needs at the right time, the right place, and in the right context, your business can become more profitable. 3. For whom is SAS RTDM designed? It provides distinct capabilities for marketers who define communication strategies, executives who need reports on marketing effectiveness, business analysts who model and predict customer behavior, and campaign managers who create target customer segments. -The following are the key benefits of RTDM: • Makes the right decisions every time, all the time. • Realizes customer needs with the right offer, at the right time, in the right channel. • Better allocates valuable IT resources. -The key features according to SAS Inc. are: • Real-time analytics. • Rapid decision process construction. • Enterprise data throughout. • Campaign testing. • Automated self-learning analytical process. • Connectivity.

The U.S. - China Competition: Who will control AI?

At the moment, U.S. companies are ahead of Chinese companies. However, this situation may be changed in the future due to the huge investments in AI in China and the support provided by the Chinese government.

Ten Top Safe and at Risk Occupations

Low-Risk Jobs -0.0036 First-Line supervisors of firefighting and prevention workers -0.0036 Oral and maxillofacial surgeons -0.0035 Healthcare social workers -0.0035 Orthotists and prosthetists -0.0033 Audiologists -0.0031 Mental health and substance abuse social workers -0.0030 Emergency management directors -0.0030 First-Line supervisors of mechanics, installers, and repairers -0.0028 Recreational therapists High risk jobs -0.99 Telemarketers -0.99 Title examiners, abstractors, and searchers -0.99 Sewers, hand -0.99 Mathematical technicians -0.99 Insurance underwriters -0.99 Watch repairer -0.99 Cargo and freight agents -0.99 Tax preparers -0.99 Photographic process workers and processing machine operators -0.99 New account clerks SOME MORE JOB LOSSES OBSERVATIONS • Kelly (2018) predicts that robots could eliminate many Las Vegas jobs. And indeed, in many casinos worldwide, you can play several traditional games on machines • People with doctoral degrees have a 13 percent chance of being replaced by robots and AI versus 74 percent for those with only a high school education (Kelly, 2018) • Women will lose more jobs to automation than men (Krauth, 2018)

The friendly AI

according to which AI machines should be designed so that they will benefit humans rather than harm them (i.e., use a system of checks and balances in designing the AI capabilities).

Successful tips for implementing AI (McKinsey study)

• Digital capabilities need to come before AI. • Machine learning is powerful, but it is not the solution to all problems. • Do not put technology teams solely in charge of intelligent technologies. • Adding a business partner may help with AI-based projects. • Prioritize a portfolio approach to AI initiatives. • The biggest challenges will be people and business processes. • Not every business is using intelligent systems, but almost all those that use them increase income and profit. • Top leadership support is necessary for a transformation to AI.

Additional Ethical Issues of Intelligent Systems

• Electronic surveillance. • Ethics in business intelligence (BI) and AI systems design. • Software piracy. • Invasion of individuals' privacy. • Use of proprietary databases and knowledge bases. • Use of personal intellectual property such as knowledge and expertise for the benefits of companies and the payment to the contributors. • Accuracy of data, information, and knowledge. • Protection of the rights of users. • Accessibility to information by AI users. • The amount of decision making to delegate to intelligent machines. • How AI can fail due to inappropriate ethics. • The ethics of legal analytics (Goldman, 2018).

Position of AI Dystopia - pessimistic approach to AI

• Elon Musk: "We need to be super careful with AI. Potentially more dangerous than nukes." Musk predicts that World War III will start because of AI. "Robots will kill us all, one day," he said in his several presentations. • Bill Gates: "I am in the camp that is concerned about super intelligence. Musk and some others are on this and I don't understand why some people are not concerned." (Comments made on TV and interviews, several times). He also suggested taxing the manufacturers and users of robots and other AI machines. • Stephen Hawking: The late scientist stated, "The development of full artificial intelligence could spell the end of the human race."

Intelligent Systems' Impact on Managers' Activities, Performance, and Job Satisfaction

• Less expertise (experience) is required for making many decisions. • Faster decision making is possible because of the availability of information and the automation of some phases in the decision-making process • Less reliance on experts and analysts is required to provide support to top managers and executives. Today, they can decide by themselves with the help of intelligent systems. • Power is being redistributed among managers. (The more information and analysis capability they possess, the more power they have.) • Support for complex decisions makes solutions faster to develop and of better quality. • Information needed for high-level decision making is expedited or even self-generated. • Automation of routine decisions or phases in the decision-making process (e.g., for frontline decision making and using automated decision making) may eliminate some managers.

Intelligent systems may create massive job losses

• They are moving very fast. • They may take a large variety of jobs, including many white-collar and nonphysical jobs. • Their comparative advantage over manual labor is very large and growing rapidly • They are already taking some professional jobs from financial advisors, paralegals, and medical specialists. • The capabilities of AI are growing rapidly. • In Russia, robots are already teaching mathematics in schools (some do a better job than humans). Just think about what could happen to the teaching profession. .

Examples of Legal issues

• What is the value of an expert opinion in court when the expertise is encoded in a computer? • Who is liable for wrong advice (or information) provided by an intelligent application? For example, what happens if a physician accepts an incorrect diagnosis made by a computer and performs a procedure that results in the death of a patient? • What happens if a manager enters an incorrect judgment value into an intelligent application and the result is damage or a disaster? • Who owns the knowledge in a knowledge base (e.g., the knowledge of a chatbot)? • Can management force experts to contribute their expertise to an intelligent system? How will they be compensated? • Is it okay for self-driving cars with in-vehicle back-up drivers to drive on public roads? (Yes, in a few states, notably in California.) -Who should regulate driverless cars: cities, states, or the federal government? -U.S. federal regulators are creating national laws for self-driving cars (for safe driving). • Should delivery robots be allowed on sidewalks? (Not in San Francisco but in some European cities) • Are drivers of Uber and similar companies self-employed? (Not in London, the United Kingdom) • Should robots have human rights? (What if they are citizens like Sophia in Saudi Arabia?) If they get rights, should they have legal responsibilities as well? • Should we legalize robot taxis? Would this make trips cheaper? (Yes in Singapore and other places, and it can be cheaper)

Legal, Privacy and Ethical Issues

•As data science, analytics, cognitive computing, and AI grow in reach and pervasiveness, everyone may be affected by these applications •Just because something is doable through technology does not make it appropriate, legal, or ethical •Data science and AI professionals/manager must be aware of these concerns •Legality versus Privacy versus Ethics, something legal may not be ethical