Uniform data entry promises legibility and uniform structure. Electronic medical records software today allows summary reports to be compiled automatically from the facts collected in individual electronic medical records. Summary reports also allow crosspatient analysis, deep algorithmic study of prognoses by classes of patients, and identification of risk factors before treatment becomes necessary.
Mining of medical data and application of deep learning algorithms have led to an explosion of interest in so-called cognitive computing for health care. And IBM has announced the Medical Sieve system, which analyzes radiological scans as well as written records. Further Reading Ayers, W. Hochberg, and C. Bleich, Howard L. Morris F.
Collen, and Automated Multiphasic Testing. Collen, Morris F. Mesko, Bertalan. Roberts, N. Gitman, L. Warshaw, R. Bruce, J. Stamler, and C. Automatic Film Editing Automatic film editing is a process by which an algorithm, trained to follow basic rules of cinematography, edits and sequences video in the assembly of completed motion pictures.
Automated editing is part of a broader effort to introduce artificial intelligence into movie making, sometimes called intelligent cinematography. Already by the mids, the influential filmmaker Alfred Hitchcock could imagine that an IBM computer might one day be capable of turning a written screenplay into a finished film.
Hitchcock invented many of the principles of modern moviemaking. One well-known rule of thumb, for instance, is his assertion that, where possible, the size of a person or object in frame should be proportional Automatic Film Editing 25 to their importance in the story at that particular point in time. Such rules over time became codified as heuristics governing shot selection, cutting, and rhythm and pacing. The first artificial intelligence film editing systems developed from these human-curated rules and human-annotated movie stock footage and clips.
IDIC has been used to generate hypothetical Star Trek television trailers assembled from a human-specified story plan centered on a particular plot point. Several film editing systems rely on idioms, that is, conventional procedures for editing and framing filmed action in specific situations. The idioms themselves will vary based on the style of film, the given context, or the action to be portrayed.
In this way, the knowledge of expert editors can be approached in terms of case-based reasoning, using a past editing recipe to solve similar current and future problems. Editing for fight scenes follows common idiomatic pathways, as does ordinary conversations between characters. This is the approach modeled by Li-wei He, Michael F. Cohen, and David H. More recently, researchers have been working with deep learning algorithms and training data pulled from existing collections of recognized films possessing high cinematographic quality, to create proposed best cuts of new films.
Many of the newer applications are available on mobile, drone, or handheld equipment. Easy automatic video editing is expected to make the sharing of short and interesting videos, assembled from shots made by amateurs with smartphones, a preferred medium of exchange over future social media. That niche is currently occupied by photography. Automatic film editing is also in use as an editing technique in machinima films made using 3D virtual game engines with virtual actors.
Frana See also: Workplace Automation. Aire-la-Ville, Switzerland: Eurographics Association. He, Li-wei, Michael F. Autonomous and Semiautonomous Systems Autonomous and semiautonomous systems are generally distinguished by their reliance on external commands for decision-making. They are related to conditionally autonomous systems and automated systems. Conditionally autonomous systems function autonomously under certain conditions.
Semiautonomous and autonomous systems autonomy are also distinct from automated systems automation. Systems are considered automated when their actions, and alternatives for action, are predetermined in advance as responses to specific inputs. An example of an automated system is an automatic garage door that stops closing when a sensor detects an obstruction in the path of the door.
Inputs can be received via not only sensors but also user interaction. An example of a user-initiated automatic system would be an automatic dishwasher or clothes washer where the human user specifies the sequences of events and behaviors through a user interface, and the machine then proceeds to execute the commands according to predetermined mechanical sequences.
In contrast, autonomous systems are those systems wherein the ability to evaluate circumstances and select actions is internal to the system. In considering real-world examples of systems, automated, semiautonomous, and autonomous are categories that have some overlap depending on the nature of the tasks under consideration and upon the specifics of decision-making.
Lastly, the extent to which these categories apply depends upon the scale and level of the activity under consideration.
While the rough distinctions outlined above between automated, semiautonomous, and autonomous systems are generally agreed upon, ambiguity exists where Autonomous and Semiautonomous Systems 27 these system categories are present in actual systems.
One example of such ambiguity is in the levels of autonomy designated by SAE formerly the Society of Automotive Engineers for driverless cars. A single system may be Level 2 semiautonomous, Level 3 conditionally autonomous, or Level 4 autonomous depending on road or weather conditions or upon circumstantial indices such as the presence of road barriers, lane markings, geo-fencing, surrounding vehicles, or speed.
Autonomy level may also depend upon how an automotive task is defined. In this way, the classification of a system depends as much upon the technological constitution of the system itself as the circumstances of its functioning or the parameters of the activity focus. Cruise control functionality is an example of an automated technology.
The user sets a speed target for the vehicle and the vehicle maintains that speed, adjusting acceleration and deceleration as the terrain requires.
Systems are capable of interpreting many potential inputs surrounding vehicles, lane markings, user input, obstacles, speed limits, etc. Within this system, the human user is still enrolled in decision-making, monitoring, and interventions.
Once a goal is established e. Behaviors internal to the activity the activity is defined by the goal and the available means are regulated and controlled without the participation of the human user. Finally, an autonomous system possesses fewer limitations than conditional autonomy and entails the control of all tasks in an activity.
Like conditional autonomy, an autonomous system operates independently of a human user within the activity structure. Autonomous Robotics Examples of autonomous systems can be found across the field of robotics for a variety of purposes. There are a number of reasons that it is desirable to replace or 28 Autonomous and Semiautonomous Systems augment humans with autonomous robots, and some of the reasons include safety for example, spaceflight or planetary surface explorationundesirable circumstances monotonous tasks such as domestic chores and strenuous labor such as heavy liftingor where human action is limited or impossible search and rescue in confined conditions.
As with automotive applications, robotics applications may be considered autonomous within the constraints of a narrowly defined domain or activity space, such as a manufacturing facility assembly line or home.
Like autonomous vehicles, the degree of autonomy is conditional upon the specified domain, and in many cases excludes maintenance and repair. However, unlike automated systems, an autonomous robot within such a defined activity structure will act to complete a specified goal through sensing its environment, processing circumstantial inputs, and regulating behavior accordingly without necessitating human intervention.
Current examples of autonomous robots span an immense variety of applications and include domestic applications such as autonomous lawn care robots and interplanetary exploration applications such as the MER-A and MER-B Mars rovers.
Semiautonomous Weapons Autonomous and semiautonomous weapon systems are currently being developed as part of modern warfare capability. Like the above automotive and robotics examples, the definition of, and distinction between, autonomous and semiautonomous varies substantially on the operationalization of the terms, the context, and the domain of activity. Consider the landmine as an example of an automated weapon with no autonomous capability.
It responds with lethal force upon the activation of a sensor and involves neither decision-making capability nor human intervention. In contrast, a semiautonomous system processes inputs and acts accordingly for some set of tasks that constitute the activity of weaponry in conjunction with a human user.
Together, the weapons system and the human user are necessary contributors to a single activity. They may also include navigating toward a target, positioning, and reloading. In a semiautonomous weapon system, these tasks are distributed between the system and the human user.
By contrast, an autonomous system would be responsible for the whole set of these tasks without requiring the monitoring, decision-making, or intervention of the human user once the goal was set and the parameters specified. By these criteria, there are currently no fully autonomous weapons systems. However, as noted above, these definitions are technologically as well as socially, legally, and linguistically contingent. Most conspicuously in the case of weapons systems, the definition of semiautonomous and autonomous systems has ethical, moral, and political significance.
The sources of agency and decision-making may also be opaque as in the case of machine learning algorithms. Autonomous systems are theoretically simpler user-interface challenges insofar as once an activity domain is defined, control and responsibility are binary either the system or the human user is responsible. Here the challenge is reduced to specifying the activity and handing over control. Semiautonomous systems present more complex challenges for the design of user-interfaces because the definition of an activity domain has no necessary relationship to the composition, organization, and interaction of constituting tasks.
An illustrative example is an obstacle detection task in which a semiautonomous system relies upon avoiding obstacles to move around an environment. The obstacle detection mechanisms camera, radar, optical sensors, touch sensors, thermo sensors, mapping, etc. In addition to the issues above, other considerations for designing semiautonomous and autonomous systems specifically in relation to the ethical and legal dimensions complicated by the distribution of agency across developers and users include identification and authorization methods and protocols.
The problem of identifying and authorizing users for the activation of autonomous technologies is critical where systems, once initiated, no longer rely upon continual monitoring, intermittent decision-making, or intervention. Further Reading Antsaklis, Panos J. Passino, and Shyh Jong Wang. Bekey, George A. Norman, Donald A. A Distinction without a Difference? SAE International. SAE International Standard.
Autonomous Weapons Systems, Ethics of Autonomous weapons systems AWS involve armaments that are programmed to make decisions without continuous input from their programmers. These decisions include, but are not limited to, navigation, target selection, and when to engage with enemy combatants.
The imminent nature of this technology has led to many ethical considerations and debates about whether they should be developed and how they should be used. This movement is still active today. Other scholars and military strategists point to strategic and resource advantages of AWS that lead to support for their continued development and use.
Those scholars who are proponents of further technology development in these areas focus on the positive aspects that a military power can gain from the use of AWS. These systems have the potential to lead to less collateral damage, fewer combat casualties, the ability to avoid unnecessary risk, more efficient military operations, decreased psychological damage to soldiers from combat, as well as bolstering armies that tend to have dwindling human numbers.
In other words, they focus on the benefits to the military that will end up using the weapon. These conversations tend to include the basic assumption that the goals of the military are themselves ethically worthy. AWS may lead to fewer civilian casualties as the systems are able to make decisions more quickly than their human counterparts; however, this is not necessarily guaranteed with the technology as the decisionmaking processes of AWS may lead to increased civilian casualties rather than the reverse.
However, if they are able to prevent civilian deaths and the destruction of property more than traditional combat, this means that they are more efficient and therefore desirable. Another way they may increase efficiency is through minimizing resource waste in times of conflict. Transporting people and the supplies needed to sustain them is an inefficient and difficult aspect of war. AWS provide a solution to difficult logistic problems.
Drones and other autonomous systems do not need rain gear, food, water, or access to health care, making them less cumbersome and thereby potentially more effective in achieving their goals. In these and other ways, AWS are seen as reducing waste and providing the best possible outcome in a combat scenario. Just War Theory focuses on when it is ethically permissible or required for a military power to engage in war and theorizes about what actions Autonomous Weapons Systems, Ethics of 31 are ethically permitted in times of war.
If it is permissible to use an autonomous system in a military attack, it is only permissible to do so if the attack itself is justified. According to this consideration, the how of being killed is less important than the why. Those who deem AWS as ethically impermissible focus on the inherent risks of such technology. These include scenarios where enemy combatants obtain the weaponry and use it against the military power that deploys them or when there is increased and uncontrolled collateral damage, reduced ability of retaliation against enemy combatant aggressorsand loss of human dignity.
A major concern is whether it is compatible with human dignity on being killed by a machine without a human as the ultimate decision-maker. It seems that there is something dehumanizing to be killed by an AWS that was provided with little human input.
Another major concern is the risk factor, including the risk to the user of the technology that if there is a situation in which the AWS is shut down either through a malfunction or an attack by an enemy it will be confiscated and MP3) used against the owner. Just War is also a concern for those who condemn the use of AWS. Just War Theory explicitly prohibits the targeting of civilians by military agents; the only legitimate military targets are other military bases or persons.
However, the advent of autonomous weaponry may mean that a state, especially one that does not have access to AWS, will not be able to respond to military strikes made by AWS. In an imbalanced situation where one side has access to AWS and another does not, it is necessarily the case that the side lacking the weapons will not have a legitimate military target, meaning that they must either target nonmilitary civilian targets or not respond at all.
Neither option is ethically or practically viable. Generally, it is accepted that automated weaponry is imminent, and so another aspect of the ethical consideration is how to regulate its use. Some are proponents of an international ban on the technology; although this is generally deemed as naive and therefore implausible, these often focus on the UN prohibition against blinding lasers, which has been agreed upon by states. Rather than focus on establishing a complete ban, others focus on creating an international treaty that regulates the legitimate use of these systems with sanctions and punishments for states that violate these norms.
Currently no such agreement exists, and each state must determine for itself how it wants to regulate the use of these systems. Further Reading Arkin, Ronald C. Leveringhaus, Alex. Sparrow, Robert.
Autonomy and Complacency Machine autonomy and human autonomy and complacency are interlinked concepts. As artificial intelligences are programmed to learn from their own experiences and data input, they are arguably becoming more autonomous. Machines that gather more abilities than their human counterparts tend to become more reliant on these machines to both make decisions and respond appropriately to novel scenarios.
This reliance on the decision-making processes of AI systems can lead to diminished human autonomy and over-complacency. Autonomous machines are those that can act in unsupervised environments, adapt to their circumstances and new experiences, learn from past mistakes, and determine the best possible outcomes in each situation without new input from programmers.
In other words, these machines learn from their experiences and are in some ways capable of reaching beyond their initial programming.
The idea is that it is impossible for programmers to anticipate every scenario that a machine equipped with AI may face congruent with its actions and so it must be able to adapt. However, this is not universally accepted as some argue that the very adaptability of these programs is not beyond their programming, as their programs are built to be adapted.
These arguments are exacerbated by the debate about whether any actor, including human beings, can express free-will and act autonomously. The autonomy of AI programs is not the only aspect of autonomy that is being considered with the advent of the technology.
There are also concerns about the impact on human autonomy as well as concerns about complacency regarding the machines. As AI systems become better adapted to anticipating the desires and preferences of the people, they serve the people who benefit from the choice of the machine becoming moot as they no longer have to make choices. Significant research has been done on the interaction of human workers with automated processes.
Studies have found that human beings are likely to miss issues in these processes, especially when these processes become routinized, which leads to an expectation of success rather than an anticipation of failure. This anticipation of achievement leads to the operators or supervisors of the automated processes to trust faulty readouts or decisions of the machines, which can lead to ignored errors and accidents.
Bahner, J. Lawless, W. Autonomy and Intelligence: A Threat or Savior? Cham, Switzerland: Springer. Parasuraman, Raja, and Dietrich H. B Battlefield AI and Robotics Generals on the modern battlefield are witnessing a potential tactical and strategic revolution due to the advancement of artificial intelligence AI and robotics and their application to military affairs.
Robotic devices, such as unmanned aerial vehicles UAVsalso known as drones, played a major role in the wars in Afghanistan — and Iraq —as did other robots.
It is conceivable that future wars will be fought without human involvement. Autonomous machines will engage in battle on land, in the air, and under the sea without human control or direction. While this vision still belongs to the realm of science fiction, battlefield AI and robotics raises a variety of practical, ethical, and legal questions that military professionals, technological experts, jurists, and philosophers must grapple with.
There are, however, many uses for battlefield AI technology that do not involve killing. The most prominent use of such technology in recent conflicts has been nonviolent in nature. UAVs are most often used for monitoring and reconnaissance.
Other robots, such as the PackBot manufactured by iRobot the same company that produces the vacuum-cleaning Roombaare used to detect and examine improvised explosive devices IEDsthereby aiding in their safe removal. Robotic devices are capable of traversing treacherous ground, such as the caves and mountain crags of Afghanistan, and areas too dangerous for humans, such as under a vehicle suspected of being rigged with an IED.
The ubiquity of IEDs and mines on the modern battlefield make these robotic devices invaluable. Another potential, not yet realized, life-saving capability of battlefield robotics is in the field of medicine. Robots can safely retrieve wounded soldiers on the battlefield in places unreachable by their human comrades, without putting their own lives at grave risk. Robots can also be used to carry medical equipment and medicines to soldiers on the battlefield and potentially even perform basic first aid and other emergency medical procedures.
It is in the realm of lethal force that AI and robotics have the greatest potential to alter the battlefield—whether on land, sea, or in the air. The Aegis Combat System ACS is an example of an automatic system currently deployed on destroyers and other naval combat vessels by numerous navies throughout the world.
The system can track incoming threats—be they missiles from the surface or air or mines or torpedoes from the sea—through radar and sonar. The system is integrated with a powerful computer system and has the capability to destroy Battlefield AI and Robotics 35 identified threats with its own munitions.
Though Aegis is activated and supervised manually, the system has the capability to act independently, so as to counter threats more quickly than would be possible for humans. In addition to such partially automated systems such as the ACS and UAVs, the future may see the rise of fully autonomous military robots capable of making decisions and acting of their own accord. At one end of the scale are robots programmed to function automatically, but in response to a given stimulus and only in one way.
A mine that detonates automatically when stepped on is an example of this level of autonomy. Also, at the lower end of the spectrum are remotely controlled machines that, while unmanned, are remotely controlled by a human.
Semiautonomous systems are found near the middle of the spectrum. These systems may be able to function independently of a human being, but only in limited ways. An example of such a system is a robot directed to launch, travel to a specified location, and then return at a given time. Semiautonomous devices may also be programmed to complete part of a mission and then to wait for additional inputs before proceeding to the next level of action.
The final stage is full autonomy. Fully autonomous robots are programmed with a goal and can carry out that goal completely on their own. In battlefield scenarios, this may include the ability to employ lethal force without direct human instruction. Lethally equipped, AI-enhanced, fully autonomous robotic devices have the potential to completely change the modern battlefield.
Military ground units comprising both human beings and robots, or only robots with no humans at all, would increase the size of militaries. Small, armed UAVs would not be limited by the need for human operators and would be gathered in large swarms with the potential ability to overwhelm larger, but less mobile, forces. Such technological changes would necessitate similarly revolutionary changes in tactics, strategy, and even the concept of war itself.
As this technology becomes more widely available, it will also become cheaper. This could upset the current balance of military power.
Even relatively small countries, and perhaps even some nonstate actors, such as terrorist groups, may be able to establish their own robotic forces.
Fully autonomous LAWs raise a host of practical, ethical, and legal questions. Safety is one of the primary practical concerns. A fully autonomous robot equipped with lethal weaponry that malfunctions could pose a serious risk to anyone in its path.
Fully autonomous missiles could conceivably, due to some mechanical fault, go off course and kill innocent people. Any kind of machinery is liable to unpredictable technical errors and malfunctions. With lethal robotic devices, such problems pose a serious safety risk to those who deploy them as well as innocent bystanders. Even aside from potential malfunctions, limitations in programming could lead to potentially calamitous mistakes.
Programming robots to distinguish between combatants and noncombatants, for example, poses a major difficulty, and it is easy to imagine mistaken identity resulting in inadvertent 36 Battlefield AI and Robotics casualties. The ultimate worry, however, is that robotic AI will advance too rapidly and break away from human control. LAWs raise serious legal dilemmas as well.
Human beings are subject to the laws of war. Robots cannot be held liable, criminally, civilly, or in any other way, for potential legal violations. This poses the potential, therefore, of eliminating accountability for war crimes or other abuses of law. Such issues require thorough consideration prior to the deployment of any fully autonomous lethal machine.
Apart from legal matters of responsibility, a host of ethical considerations also require resolution. Will autonomous robots be able to differentiate between a child and a soldier or recognize the difference between an injured and defenseless soldier and an active combatant? Can a robot be programmed to act mercifully when a situation dictates, or will a robotic military force always be considered a cold, ruthless, and merciless army of extermination?
Since warfare is fraught with moral dilemmas, LAWs engaged in war will inevitably be faced with such situations. Experts doubt lethal autonomous robots can ever be depended upon to take the correct action. Moral behavior requires not only rationality—something that might be programmed into robots—but also emotions, empathy, and wisdom. These latter things are much more difficult to write into code. The legal, ethical, and practical concerns raised by the prospect of ever more advanced AI-powered robotic military technology has led many people to call for an outright ban on research in this area.
Others, however, argue that scientific progress cannot be stopped. Instead of banning such research, they say, scientists and society at large should look for pragmatic solutions to those problems. Some claim, for example, that many of the ethical and legal problems can be resolved by maintaining constant human supervision and control over robotic military forces. Others point out that direct supervision is unlikely over the long run, as human cognition will not be capable of matching the speed of computer thinking and robot action.
There will be an inexorable tendency toward more and more autonomy as the side that provides its robotic forces with greater autonomy will have an insurmountable advantage over those who try to maintain human control. Fully autonomous forces will win every time, they warn. Though still in its emergent phase, the introduction of continually more advanced AI and robotic devices to the battlefield has already resulted in tremendous change.
Battlefield AI and Robotics have the potential to radically alter the future of war. It remains to be seen if, and how, the technological, practical, legal, and ethical limitations of this technology can be overcome. William R.
Further Reading Borenstein, Jason. Morris, Zachary L. Scharre, Paul. Singer, Peter W. London: Penguin. Bayesian Inference Bayesian inference is a way to calculate the probability of the validity of a proposition based on a prior estimate of its probability plus any new and relevant data. The Bayesian theorem remains useful to artificial intelligence in the twenty-first century and has been applied to problems such as robot locomotion, weather forecasting, jurimetrics the application of quantitative methods to lawphylogenetics the evolutionary relationships among organismsand pattern recognition.
It is also useful in solving the famous Monty Hall problem and is often utilized in email spam filters. As Lusted later remembered, medical knowledge in the mid-twentieth century was usually presented as symptoms associated with a disease, rather than as diseases associated with a symptom. Bayesian statistics are conditional, allowing one to determine the chance that a certain disease is present given a certain symptom, but only with prior knowledge of how often the disease and symptom are correlated and how often the symptom is present in the absence of the disease.
It is very close to what Alan Turing described as the factor in favor of the hypothesis provided by the evidence.
The first practical demonstration of the theorem in generating the posterior probabilities of particular diseases came in Warner and his staff applied the theorem to determine the probabilities by which an undiagnosed patient with definable symptoms, signs, or laboratory results might fit into previously established disease categories.
The computer program could be used over and over as new information presented itself, establishing or ranking diagnoses by serial observation. The Bayesian model has been extended and modified many times in the last half century to account or correct for sequential diagnosis and conditional independence and to weight various factors. Bayesian diagnostic assistants have also been critiqued for their shortcomings outside of the populations for which they were designed.
A nadir in use of Bayesian statistics in differential diagnosis was reached in the mids when rule-based decision support algorithms became more popular. Bayesian methods recovered in the s and are widely used today in the field of machine learning. Artificial intelligence researchers have extracted rigorous methods for supervised learning, hidden Markov models, and mixed methods for unsupervised learning from the idea of Bayesian inference.
In a practical context, Bayesian inference has been used controversially in artificial intelligence algorithms that attempt to determine the conditional probability of a crime being committed, to screen welfare recipients for drug use, and to detect potential mass shooters and terrorists. The approach has again faced scrutiny, particularly when the screening involves rare or extreme events, where the AI algorithm can behave indiscriminately and identify too many individuals as at-risk of engaging in the Beneficial AI, Asilomar Meeting on 39 undesirable behavior.
Bayesian inference has also been introduced into the courtroom in the United Kingdom. In Regina v. The circle of historic luminaries who perceived value in the Bayesian approach to probability included Pierre-Simon Laplace, the Marquis de Condorcet, and George Boole. Rather counterintuitively, the chances of winning under conditional probability are twice as large by switching doors. Further Reading Ashley, Kevin D. Barnett, G. Bayes, Thomas. Donnelly, Peter. Fox, John, D.
Barber, and K. Ledley, Robert S. Lusted, Lee B. Warner, Homer R. Toronto, and L. The Asilomar Conference on Beneficial AI took on this question, moving beyond the Three Laws and the Zeroth Law MP3) establishing twenty-three principles to safeguard humanity with respect to the future of AI.
The Future of Life Institute, sponsor of the conference, hosts the principles on their website and has gathered 3, signatures supporting the principles from AI researchers and other interdisciplinary supporters.
The principles fall into three main categories: research questions, ethics and values, and longerterm concerns. Those principles related to research aim to ensure that the goals of artificial intelligence remain beneficial to humans.
They are intended to guide financial investments in AI research. To achieve beneficial AI, Asilomar signatories contend that research agendas should support and maintain openness and dialogue between AI researchers, policymakers, and developers. Researchers involved in the development of artificial intelligence systems should work together to prioritize safety. Proposed principles related to ethics and values are meant to reduce harm and encourage direct human control over artificial intelligence systems.
Parties to the Asilomar principles ascribe to the belief that AI should reflect the human values of individual rights, freedoms, and acceptance of diversity.
In particular, artificial intelligences should respect human liberty and privacy and be used solely to empower and enrich humanity. AI must align with the social and civic standards of humans. The Asilomar signatories maintain that designers of AI need to be held responsible for their work.
One noteworthy principle addresses the possibility of an arms race of autonomous weapons. The creators of the Asilomar principles, noting the high stakes involved, included principles covering longer term issues.
They urged caution, careful planning, and human oversight. Superintelligences must be developed for the larger good of humanity, and not MP3) to advance the goals of one company or nation. Together, the twenty-three principles of the Asilomar Conference have sparked ongoing conversations on the need for beneficial AI and specific safeguards concerning the future of AI and humanity. Diane M. Robots and Empire. Sarangi, Saswat, and Pankaj Sharma.
Abingdon, UK: Routledge. Heck, I can't even get dressed in the morning without my mom telling me what to wear. Kardashian added that she and her sisters help tabloid editors come up with supposedly scandalous headlinespushing sales of those magazine and then taking to their blogs to refute the rumors and garner sympathy from fans. It's a circular tactic that Kim says she learned from former best friend Paris Hilton, adding:.
My Facebook followers even believed I was actually confiding in them. Everybody was winning Turns out, my soul had been lost a long time ago. Kim says she will donate all the money she's earned from Tweeting product names to those who tried QuickTrim because they believed it was a healthy weight loss supplement.
I'm a multi-millionaire with no real job. I lost all this weight because I had the time to work out and the money to pay a personal trainer. It's taken a very long time, but THG applauds Kim Kardashian for finally telling the truth about all the fallacies in her life. We'd also like to say Simpson murder him. Their leaders have been assassinated. Their communities are flooded with drugs and weapons. They are overly policed and incarcerated. All over the world our people are suffering because they don't have the tools to fight back.
ELN rebels took the embassy. Security got me out, but the rebels took hostages. Nick was Deputy Chief of the S. They stormed the basement, and what do they find? They find it empty. Nick had ignored my direct order, and carried out an unauthorized military operation on foreign soil; and saved the lives of over a dozen political officers, including my daughter.
When we were at that away tournament in Philly? She was MP3) leading scorer. February see other referencesmaking Ducasse's date of birth c. February Eka Darville's age at the times of filming Jessica Jones : Season 1The Defenders : Season 1and Jessica Jones : Season 2working back from the times of filming, would place Ducasse's date of birth a little earlier, around Februaryso it can be assumed that due to the slight leniency of the comment, Ducasse is slightly older than Phillip Jones, born around January His date of death is April 13, see s referencesmeaning he was born between January 1, and April 13,making his date of birth approximately February With his date of birth approximated to April see s referencesspecifically April 11,this can be taken as roughly May 11, With his date of birth approximated to November see s referencesspecifically November 20,the middle of Jones' time as a year-old as an approximation for when he met Dillard would be May 21, The photo being taken is dated to approximately May 12, see other referencesso this would suggest approximately May 12, for when they met.
Putting more weight in the specific date than just the year, a weighted calculation gives roughly May 24, for when they met. With Ellerh born around July see s referencesthis would be June This means that Rand and Davos overlap in age.
With Rand born on April 1, see other referencesthis means Davos was born between April 2, and April 1, With Sacha Dhawan's ages at the times of filming Iron Fist : Season 1 and Season 2working back from the settings, his age would suggest Davos being born closer toso this would imply that Davos was born closer to April 2, than April 1, It can be calculated that he was born roughly around August With Dumont's date of birth approximated to March see s referencesshe would have been 9 from March to Marchsuggesting her fall was around September Reagan Grella, who plays young Dumont, was 8 at the time of filming, suggesting Dumont is closer to 9.
A weighted calculation would overall place her fall around August 24, However, Hannah Hardin's age at the time of filming Lotus Eatersworking back from the February setting, would suggest Mina Hess was born around May and is 15 in the flashback.
Taking a weighted average, overall Mina Hess' date of birth can be placed around Septembermaking her 18 in the flashback and in present events. With his death dated to Mayhis date of birth would be approximately November With Robert leaving dated to May 30, see s referencesDanny would therefore have been born between May 31, and May 30,so his date of birth can be approximated to November This cannot refer to the mids flashback in The Creatoras this is over 30 years beforeso he must have just been formally hired as their regular lawyer at a later date.
This would mean his year of birth would be This fits what is said by Ward Meachum in Shadow Hawk Takes Flightthat Danny is in his "mids," he would be 24 going on 25, and in Rolling Thunder Cannon Punchwhere Danny's grave shows his birth year as "" with the last number obscured.
With his birthday reasoned to be around late Octoberthis would put him learning to pilot the ship at around late April With his death dated to December 3, see referencesRocha would have been born between December 4, and December 3,so approximately June With her death dated to December 7, see s referencesScolari would have been born between December 8, and December 7,so approximately June With her death dated to December 9, see referencesHwang would have been born between December 10, and December 9,so approximately June With Nadeem's date of birth approximated to December see s referencesthe middle of his time as a year-old as an approximation for this would have been roughly June To see the maths and calculations, check here.
W'Kabi later says, "For 30 years your father was in power and did nothing," referring to Klaue, and to the time that spanned between his attack and T'Chaka 's death, dated to June 22, As well as this, W'Kabi says in a deleted sceneon July 4,that when it comes to Klaue, for "30 years, there's been no justice". While these pieces of dialogue would imply the attack was aroundthe film also shows scenes set in "" which depict the attack as having been recent.
Weighted calculations from all the evidence and factors gives April 24, as the approximate best-fitting date for the attack, and January 15, as the approximate best-fitting date for the "" scenes. The calculations for these dates and the other events are all relative to each other, and can be found in detail here. Putting more weight on specifically 3 years rather than just general, a Minoru (7) - Rise Of Nightmares (File average gives him starting collecting the intel as approximately June 18, With Russo's date of birth approximated to July see s referencesthis event can be approximated to July - the month when Russo was both 10 and Putting more weight on the more specific, a weighted calculation gives her completion of surgeries as approximately August 6, This may be used as an approximation for when Lyonne composed the piece.
It is and sunset in Mauna Kea, and the two times in the year when sunset in Mauna Kea is are around April 20th and August 26th each year. Therefore, it is most likely August 26, However, in the scene, one other student says to another, "Dude, have you seen Reservoir Dogs yet?
Therefore, the earliest possible this scene can be is October 25, This earliest possible date should be used for it to be as close as possible to the August 26th date for the sunset, so the scene is dated to October 25, It can therefore be approximated to December 23,to avoid Christmas, which would otherwise likely come up in the MP3). With her date of birth approximated to April see s referencesspecifically April 17,and Pop's arrest approximated to April 24, see other referencesshe has to have met him between April 17, and April 24, She likely met him closer to the 17th than 24th, as her meeting him at 9 seems significant, implying she got to know him a little.
It can be estimated that they met around April 19, The full calculations can be found here. So, the finals week was May The most likely date for a finals week in was May 5,so Hogarth likely met Ross there. A weighted calculation gives roughly August 9, for Lyonne finding out. Considering how far Matt has got with learning Braille in the flashbacks of Cut Man at the time of his father's death, he likely would have been blinded around 6 months earlier, roughly May 12, The Cut Man flashback of him stitching his father before he was blinded would be around a month earlier, Saturday, April 9, This would refer to the year ofso can be approximated with the midpoint, July 2, However, it may also be used more loosely to refer to "about a year ago", so around March 20, Putting more weight in the exact meaning, a weighted calculation gives approximately May 28, for Bradley naming Poindexter MVP.
With her death dated to December 5, see referencesWong would have been born between December 6, and December 5,so approximately June In the flashbacks in Kinbakuon October 29, See s referencesMurdock tells Elektra Natchios that his father died "10 years" ago, suggesting that he died around late However, Jack Murdock died a couple of months before Stick met Matt, which was another several months before he left Matt.
If there is around 8 months between Jack's death and Stick leaving Matt, working from the midpoint between these two suggestions, mid, 4 months either way would suggest that Jack died around early and Stick left Matt around late However, the subtitles of Cut Man show Creel vs. Murdock to be November 12thso it can be shifted to the nearest November: November 12, This lines up with the fact that the poster in the episode shows it to be a Saturday, with November 12, being a Saturday. Matt and Stick can then be approximated as meeting around 2 months later, January 12,and Stick leaving Matt a further 6 months later, July 12,
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