“The infiltration of robotics and artificial intelligence (AI) in the health sector is imminent. Existing and new laws and policies will require careful analysis to ensure the beneficial use of robotics and AI, and to answer glaring questions such as, “when is it appropriate to substitute machines for caregivers?” This article begins part one by offering an overview of the current use of robots and AI in healthcare: from surgical robots, exoskeletons and prosthetics to artificial organs, pharmacy and hospital automation robots. Part one ends by examining social robots and the role of Big Data analytics. In part two, key sociotechnical considerations are discussed, and we examine their impact on medical practice overall, as the understanding and decision-making processes evolve to use AI and robots. In addition, the social valence considerations and the evidenced-based paradox both raise important policy questions related to the appropriateness of delegating human tasks to machines, and the necessary changes in the assessment of liability and negligence. In part three, we address the legal considerations around liability for robots and AI, for physicians, and for institutions using robots and AI as well as AI and robots as medical devices. Key considerations regarding negligence in medical malpractice come into play, and will necessitate an evolution in the duty and standard of care amidst the emergence of technology. Legal liability will also need to evolve as we inquire into whether a physician choosing to rely on their skills, knowledge and judgement over an AI or robot recommendation should be held liable and negligent. Finally, this paper addresses the legal, labour and economic implications that come into play when assessing whether robots should be considered employees of a health care institution, and the potential opening of the door to vicarious liability.”
“Although many are concerned that autonomous weapon systems may make war “too easy,” no one has addressed how their use may alter the distribution of the constitutional war power. Drones, cyber operations, and other technological advances in weaponry already allow the United States to intervene militarily with minimal boots on the ground, and increased autonomy in weapon systems will further reduce risk to soldiers. As human troops are augmented and supplanted by robotic ones, it will be politically easier to justify using force, especially for short-term military engagements. Accordingly, one of the remaining incentives for Congress to check presidential warmongering — popular outrage at the loss of American lives — will diminish. The integration of autonomous weapon systems into U.S. military forces will therefore contribute to the growing concentration of the war power in the hands of the Executive, with implications for the international doctrine of humanitarian intervention.”
I interviewed Prof. Ryan Calo who is the Lane Powell and D. Wayne Gittinger Associate Professor at the University of Washington School of Law. He is a faculty co-director (with Batya Friedman and Tadayoshi Kohno) of the University of Washington Tech Policy Lab, a unique, interdisciplinary research unit that spans the School of Law, Information School, and Paul G. Allen School of Computer Science and Engineering. Professor Calo’s research on law and emerging technology appears or is forthcoming in leading law reviews (California Law Review, University of Chicago Law Review, and Columbia Law Review) and technical publications (MIT Press, Nature, Artificial Intelligence) and is frequently referenced by the mainstream media (NPR, New York Times, Wall Street Journal).
Cetin: Lets begin with a personal question. Robots and law… It has become quite a popular topic. How do you evaluate the development of this field?
Calo: I am very happy with the trajectory of robotics law and policy in the past ten years. It went from being a bit of a fringe conversation, at least in the United States, to a mature sub-discipline with sophisticated theory and concrete examples. I think that We Robot—the annual conference you’ve attended—has been instrumental.
Cetin: : Countries have gradually started to determine AI policies. What do you think about the effects of the democratic and economic structure of countries on AI policies?
Calo: Good question. Some countries are seeing AI as an opportunity to be more globally competitive, whereas others are worried about preserving their edge. The best policies in my view think about the social impacts of AI on their own society while understanding AI as a global enterprise. I don’t like the rhetoric of AI as a “race” that one or more countries will “win.” This kind of thinking leads to harmful shortcuts and hinders cooperation.
Cetin: Developing countries import the technological products largely, and these technological products find a great demand in the domestic market. How do you think this situation affects AI regulations in developing countries?
Calo: I think it’s important to keep in mind that technology brings with it cultural and other assumptions. So when developed economies export technology to less developed ones, there is the potential that the values of those developed nations will accompany the product. Thus I think the AI policy of developing countries should include best practices around procurement. What I mean is that developing countries, though they may not be developing AI at the same rates, still have market power and can insist that the products they import respect their values and well-being. No entity should import AI without insisting on this.
Cetin: Comparing anglo-saxon law system with continental law system, what can the regulatory challenges of AI and robots be?
Calo: I actually think the challenges of robotics law are pretty consistent across common law and civil law. They include assessing responsibility for harm, privacy, and questions of control and ownership. It may be that common law proves more flexible in reacting to new technology but there’s no inherent reason that would be the case.
Cetin: Especially in recent years, technology companies have taken steps in artificial intelligence and ethics. As an example, one of them was Google. What should be the most important issue for companies when determining policy on artificial intelligence and ethics?
Calo: I have long argued that we cannot emphasize ethics to the exclusion of law and policy. This phenomenon has become known as “ethics washing,” which captures the intuition many have that companies would rather craft their own ethical guidelines than face mandatory rules from government. So while the content of ethics programs is very important, so is the question of legitimacy.
With this understanding in place, companies should emphasize the ways that they harms and benefits of AI are often unevenly distributed and have processes in place to co-design AI with all stakeholders and assess the social impacts of new technologies, especially on the most vulnerable. This is more important in my opinion than mere transparency.
Cetin: The European Commission recently adopted the Cyber Security Act. This is an important step about information security in EU. What about the US? How do you evaluate the approachment of the US to cyber security in the terms of private sector and government applications?
Calo: I worry that the definition of hacking is outdated in light of AI, especially adversarial machine learning. I wrote a paper about this with colleagues in computer science entitled Is Tricking a Robot Hacking? We argue that manipulating AI by tricking it is becoming just as dangerous as breaking into a computer system. We need ways to make AI more robust against attack while also protecting researchers who are testing AI for insecurity or bias.
Cetin: CCPA is the one of the most important regulations in California. But still there is no federal regulation on data protection in the US. What are the effects of this situation for individuals and companies?
Calo: I don’t know. Lots of people and groups, including companies themselves, are calling for federal baseline data protection in the United States. I think everyone is tired of the uncertainty and that fear and instability that results. I don’t the CCPA is perfect but I credit California for jump-starting the conversation in the U.S.
Cetin: I am sure this question is asked to you so much, but I ask it again for the robotic.legal readers. What are your suggestions to university students who want to improve themselves in robot law?
Calo: Great question! I would say to attend or at least watch and follow We Robot. That is where this conversation is most vibrant. But also, seek out people in other disciplines. If you’re a roboticist, find the law and social science people. If you’re in law or social science, talk to the robotics and AI students and faculty. As I say often, very few important questions exist that can be resolved by reference to any single disciplines.
Thanks for your always excellent questions, Selin, and for educating people about about robotics law!
Robotic Process as known in recent years in the world of automation Automation (RPA) is blowing. Robot technology is preparing to move to a completely different dimension with Artificial Intelligence. Robots are expected to be active in almost all areas of business life, especially in the office.
Artificial intelligence-based robots promise much more in terms of productivity than people will start a new era in business. It is inevitable that the person who has lost his expertise to the robots in the transition period will have to re-train and have new abilities. It feels great that there will be no need for continuous work in a world where the distinction of robots and people who will take on more creative tasks that surpass artificial intelligence (if possible!)
Of course, the reflections of this trend which includes many rhetorical questions along with the subject of ‘creative’ works that we need to learn in Accounting, Tax and Audit sector have reached the dimensions that will satisfy Y-Generation / digital natives. Let’s get to know the metal collars ready to be the biggest supporter of the white collars after the blue-collar co-boots.
Three industrial revolutions are fallen from the sky..
People in the arms of the 4th Industrial Revolution. The quartet of mechanization, serialization, automation and digitalization have already been engraved in the literature as words that describe these phases of revolution. In fact, every change comes with a survival guide .
“It Is Not the Strongest of the Species that Survives But the Most Adaptable” said Charles Darwin. He sealed this universal truth with his signature in 1809. It’s time to inject the first dose into our bodies, as we will face more change in next 30 years than the past 100 years of change.
ARTIFICIAL INTELLIGENCE What is this “ARTIFICIAL INTELLIGENCE”?
With the development of technology, does anyone deny that we are individuals with the idea of doing more with less in many areas? While thousands of tiny orange robots in distribution centers in the United States take packages for storage to Amazon and send them to mail when sales are made, it does not seem unlikely that the answer to the above question will not come out as yes.
The simplest description of artificial intelligence; Add a pinch computer algorithm on the character of human intelligence. A tremendous mix… How does this mechanism work? Don’t go too far. Siri, technolgy in your palm, would comprehend the logic of the idea. Any artificial intelligence, when you ask the question X, will choose the most rational one from the answers given or defined before, and will present it to you. Of course, our subject matter is not just an artificial intelligence that filters information and turns to us. Keep your imagination wide. We’re talking about a mechanical or bot that can store an enormous amount of data anywhere on the Earth, with a probability of almost zero error. Machine learning, Deep Learning and more kinds of technology.
The issue is deep so it’s time to close the brackets and free dive to our main topic, Robots and Processes. First let’s get to know who these robots are. Then let’s devote the last page of our article to RPA fans. Boss, get me a robot! Although it has a symbolic importance in addition to the recent developments, the fact that IBM’s supercomputer Deep Blue defeated Garry Kasparov in 1997 has contributed to the establishment of a relationship of trust and admiration between man and robot. After seeing what these bots were capable of, the market masters, who realized that playing chess or GO, had little impact on the developing economy, quickly turned their eyes to business. In the first place, robots that would be used in simple production and service tasks would be able to undertake much more complex tasks over time, which happened as targeted. Experts predict that by 2025, many office tasks will be carried out by robots. That’s where our story begins. To date, many employees, who have disappeared from the field of business due to automation in developed economies, had to turn to new business lines that emerged through automated processes. However, this group was more concerned with the group that we call blue collar. Nowadays, the creators emphasize that we are in a phase where artificial intelligence intensely exists in white collar jobs. Our office colleagues, referred to as metal collars, are likely to stand up to us, especially in some service areas. If the basic function of your job is to take the number in one Excel cell and move it to another cell and print this process, the robots will knock on your door soon. It is estimated that 50 percent of the current employment in the US will change in the next 20 years with developing robot technologies.
In 2045, half of the workers, civil servants and middle managers will be robots! It may happen even it is aggressive growth target. Let’s remember Hitachi, it has been four years since production managers transferred some of their tasks to ERP software. There are people who empathize with people and behave mercifully. Do you remember the Mechas in the movie of Spielberg Artifical Intelliigence? Hyundai developed wearable robots (exoskeleton) in 2017 and plans to robotize people, at least in logistics and loading areas, instead of hiring robot workers. Thus, many people will be able to continue working in factories without being unemployed. But there is a bitter truth that human evolution is progressing more slowly than machines. Considering that the performance of the processor doubles every 2 years under Moore’s law, the sentiment that we will fall back in this marathon is strong. On the other hand, the world’s most powerful and valuable resource is intelligence. Human intelligence is the only example that has the ability to imagine, design and implement in all forms of intelligence. That is why I think that the human touch at certain points will never lose its value. Although most of the artificial intelligence produced in Silicon Valley and other technology centers has a cottony feeling that most people focus on developing their talents, rather than replacing them, there is only one reality for our geography. We urgently need to move from digital immigration to digital lover.… Neither Hawking’s concern for human catastrophe nor Musk’s universal income utopia. There is only one magic phrase in the box at the end of the labyrinth: “There is no escape from the smart future”. We didn’t run.
RPA cinema proudly presents you here.
Our digital angels: “Stella Spencer, Sue, Suzy, Sunny”
Hi Spencer, can you tell the Deloitte Times readers about yourself?
In November 2018, I was coded in Deloitte Istanbul office. I’m an RPA Bot. I work as a digital accountant at Deloitte BPS with my four other bot friends.
RPA? What is this RPA? What does it mean to be a bot?
TR / Robotic Process Automation is a software technology that can simulate any process a person makes on a computer. I am software robot or bot, imitating an employee, logging into applications, entering data, completing tasks, and calculating. I’m a metal collar. I have the ability to do all the algorithmic work that the white collar can do. I am able to finish boring and repetitive jobs in 1/10 of a the white collar employee’s time and I can work 7/24 since I am a robot. A virtual ROBOT!
A traditional IT automation can do what it says, what is your difference?
I’m not part of the IT infrastructure. What distinguishes me from traditional IT automation is my ability to be aware of changing conditions, exceptions and to adapt new situations quickly. I am able to be Re-coded, designed, integrated into to the systems easily. I can work 24/7 without getting tired, taking a break, getting tired of it. For example; my job description is to make all declarations and notifications with automatic and multi-thinking systems among applications. It is my job to fill out the tax declarations from the BDP interface and send them to the relevant teams for approval by obtaining PDFs through the online system of revenue administration. Classic automation perceives a missing taxpayer data as an exception and passes it back to the personnel. I can do my own work. I integrate the relevant source system, I can add the missing data to the relevant place without the need for human intervention. I have the ability to correct myself. Sue automatically makes the job exits and entrances from SSI system. She do not need to ask the SSI passwords of the companies to anyone. When Sue is triggered by the task, she is able to find and use relevant register and password records.
It is impressive! What is the cost of a tailor sewing his own tear? I guess you have a cool salary scale, right? Do you take overtime?
My license fee is my bare salary. In the medium term, I would say I cost less than a full-time wage employer of the company. Besides, I work 24/7 and I don’t receive any overtime fee. According to statistics, there is a benefit ratio like 1 robot / 4 full staff.
Cost benefit is indisputable, so why should they prefer to hire you? Does the RPA realm have rules like the famous 3 robot rules?
First of all, it is very important that the businesses that will prefer me are homogeneous in their way of doing business. Our first ultrasound before our birth is the “Proof of Concept” certificate. If you have a frequent, repetitive, rule-based business and a standardized ecosystem, our POC values will be high.So, it means we are ready for delivery. If you have an inventory that the rules change very often or inventory can not be converted to digital or difficult to get digital data, you should not rush for us since there are gaps and non-homogeneous agents in your processes. It is the healthiest way to advance with a full RPA project after the completion of improvement of the existing processes .
Let us come to the answer to the question why you should choose us. According to the RPA constitution, we have 7 golden rules that describe our purpose of existence.
Better quality services: fewer errors and better service.
Better compliance: Business processes are shaped in accordance with existing regulations and standards.
Increased speed: Due to the reduction in processing time of robots, tasks are completed at speeds never experienced before.
Increased agility: Ability to adapt to new or changing process rules with reduced load.
Comprehensive analysis: Improved efficiency by digitizing and auditing process data.
Reduced costs: Manual or repetitive jobs are automated by RPA software. Allows competitive pricing.
Employee experience: More interesting and less ordinary, less manual work, high employee productivity.
Very good wishes, but were you able to have desired outcome in real life?
Perfectly… All declaration processes are designed to be lawful, with minimum error and zero error margins, and the processes are managed successfully. We have managed to cure the digital hunchback of accounting and tax in terms of documentation and record management. The homogeneity of the work patterns reached 100%. Automatic approvals, rejections came out of the individual monopoly. Transparency, system logs, information privacy, separation of tasks principle is experiencing the golden age. The working hours and the expenses of the working hours during the declaration periods were automatically eliminated. Our digital literacy rate increade to 100%. We have very good deal with digital collars and digital natives. The countdown has already begun for new processes.
Last word, what can you say for the future tax world?
Short and concise … Technology is the main force that allows time to flow, and those who own it now and in the future, will be the winning party as in the past.
Artificial intelligence (AI) is increasingly driving important developments in technology and business, from autonomous vehicles to medical diagnosis to advanced manufacturing. As AI moves from the theoretical realm to the global marketplace, its growth is fueled by a profusion of digitized data and rapidly advancing computational processing power, with potentially revolutionary effect: detecting patterns among billions of seemingly unrelated data points, AI can improve weather forecasting, boost crop yields, enhance detection of cancer, predict an epidemic and improve industrial productivity.
Technology trends can be discerned through patent analytics.
Drawing on WIPO’s expertise in patent data analytics, this first publication in the series WIPO Technology Trends investigates the trends in the emerging AI era: it analyzes patent, scientific publishing and other data to review past and current trends in AI, while offering insights into how innovation in this field is likely to develop in the coming years.
This publication is among the first to systematically research trends in AI technology in order to discover which fields show the largest amount of innovative AI activity, which companies and what institutions are leading AI development, and the location of future growth markets.
WIPO has devised a new framework for the understanding of developments in the field, with AI-related technologies grouped to reflect three dimensions of AI: techniques used in AI, such as machine learning; functional applications, such as speech processing and computer vision; and application fields, including telecommunications and transportation.
For each of these areas, this report provides data and analysis that identify trends, key players, geographical spread and market activity, including acquisitions and litigation. In addition, it includes contributions from AI experts from across the globe, addressing issues such as existing and potential uses and impact of AI technology, legal and regulatory questions, data protection and ethical concerns.
You can find the full document from the link below:
Researching of Criminal Responsibility of Artificial Intelligence Robots
Lawyer Melisa Aydemir
Crime and Punishment: The Journal of Criminal Law
“In this thesis, the criminal responsibilities of the robots with artificial intelligence are discussed. Many of the technological developments started by taking the internet of things, the internet of things, unified in artificial intelligence and even found themselves. We are witnessing more and more conversions and developments of robots with artificial intelligence, which we see a magnificent reflection of technological developments, and this excites us like many scientists. However, this excitement as well as a lot of obscurity. Likewise, when we question the question of bil what they can achieve usunda in the future and even today’s plan, we are able to engage ourselves in the spell of our answers, as well as in the question of how any damages / dangers can be compensated when the legal norms are violated. In the light of all these developments, if we leave aside the legal responsibility of artificial intelligence, we can declare that we feel obliged to give place to our research in order to respond to the question of what its position in criminal law would be. We hope that at the end of this thesis you will have some insight into what the penal responsibilities of artificial intelligence robots will be and what status they can take in the world of law.”
“As robots and artificial intelligence (AI) increase their influence over society, policymakers areincreasingly regulating them. But to regulate these technologies, we first need to know what they are. And here we come to a problem. No one has been able to offer a decent definition of robots and AI — not even experts. What’s more, technological advances make it harder and harder each day to tell people from robots and robots from “dumb” machines. We’ve already seen disastrous legal definitions written with one target in mind inadvertently affecting others. In fact, if you’re reading this you’re (probably) not a robot, but certain laws might already treat you as one.
Definitional challenges like these aren’t exclusive to robots and AI. But today, all signs indicate we’re approaching an inflection point. Whether it’s citywide bans of “robot sex brothels” or nationwide efforts to crack down on “ticket scalping bots,” we’re witnessing an explosion of interest in regulating robots, human enhancement technologies, and all things in between. And that, in turn, means that typological quandaries once confined to philosophy seminars can no longer be dismissed as academic. Want, for example, to crack down on foreign “influence campaigns” by regulating social media bots? Be careful not to define “bot” too broadly (like the California legislature recently did), or the supercomputer nestled in your pocket might just make you one. Want, instead, to promote traffic safety by regulating drivers? Be careful not to presume that only humans can drive (as our Federal Motor Vehicle Safety Standards do), or you may soon exclude the best drivers on the road.
In this Article, we suggest that the problem isn’t simply that we haven’t hit upon the right definition. Instead, there may not be a “right” definition for the multifaceted, rapidly evolving technologies we call robots or AI. As we’ll demonstrate, even the most thoughtful of definitions risk being overbroad, underinclusive, or simply irrelevant in short order. Rather than trying in vain to find the perfect definition, we instead argue that policymakers should do as the great computer scientist, Alan Turing, did when confronted with the challenge of defining robots: embrace their ineffable nature. We offer several strategies to do so. First, whenever possible, laws should regulate behavior, not things (or as we put it, regulate verbs, not nouns). Second, where we must distinguish robots from other entities, the law should apply what we call Turing’s Razor, identifying robots on a case-by-case basis. Third, we offer six functional criteria for making these types of “I know it when I see it” determinations and argue that courts are generally better positioned than legislators to apply such standards. Finally, we argue that if we must have definitions rather than apply standards, they should be as short-term and contingent as possible. That, in turn, suggests regulators—not legislators—should play the defining role.”
In this blog post, I argue whether, and at what level, it is possible to exercise right to personal data protection in the era of Social Robots with Artificial Intelligence (hereafter, Social Robot). I analyze the concept of consent that was strengthened in European Union’s General Data Protection Regulation (GDPR). I basically reach to such a conclusion that, a Social Robot at personal usage challenges practicability of the GDPR. This conclusion derives from, first, Social Robot’s ability to collect vast amount of data naturally, e.g. via natural Human-Robot Interaction, or when it connects to Internet. Since a personal Social Robot’s life source, its blood, is personal data, it would be absurd for a user to not to give consent to get more personal services. In addition, it is well-known that most of the users do not read/listen consent texts, or do not understand even if they do so. Moreover, it is not easy to answer to the question of whether consent could be validly given for purposes that even the developer is not able to foresee (Unpredictable by Design). Finally, even if consent was validly given, it is not possible to make Social Robot to “forget” about the personal data in subject, in case when a particular personal data became an organic part of robot’s Neural Network. Otherwise, how consent could be withdrawn from a Social Robot should also be questioned.