Tuesday, November 29, 2016

Health 4.0: Robots, Artificial Intelligence, and Ethics

Futurist Ray Kurzweil has predicted that computers will be as smart as humans by 2030. By 2045, he claims 'artificial intelligence' systems may be a billion times more powerful than our unaided 'human intelligence'. Artificial intelligence (AI) will be a key component of autonomous, self-learning robotic systems and ‘smart’ machines of the future. Are you prepared for what this means?

The promise of Artificial Intelligence (AI) has always been just beyond the horizon, not quite realistic yet still capturing our imagination in contemporary movies and literature. At its inception, AI was initially deployed for highly selective defense or space exploration applications. However, over time it has steadily advanced and has begun to be utilized in many other industries, such as transportation, manufacturing, and healthcare.

Health 4.0 Future Scenario: By 2040, a space-based global artificial intelligence (AI) network of satellites will be in place that will monitor and help provide healthcare to people on Earth and in colonies across our solar system on the Moon, Mars, and other locations. The system will be linked to massive global health data warehouses storing data from a wide range of health IT systems, e.g. Electronic Health Record (EHR) systems, Personal Health Records (PHR), Health Information Exchange (HIE) networks, wearable fitness trackers, implantable medical devices, clinical imaging systems, genomic databases and bio-repositories, service robots, and more.

The space-based global AI system will monitor and analyze the health data gathered on all humans in real-time, detecting potential individual and public health issues. The global AI system will detect problems, diagnose them, send alerts to patients and their healthcare providers, diagnose the problems and recommend treatment plans to resolve the healthcare issue. The system will also be interfaced to pharmacies, laboratories, health insurers, public health agencies, and other institutions as needed. The system will also be able to monitor a patient's progress, as well as adherence to recommended treatment plans. It will also seek to anticipate potential healthcare issues, provide preventive health and predictive health information tailored to each human, and even make key healthcare decisions on your behalf.

RoboEthics

How people communicate with each other is very different from how people interact with machines. A growing trend in computer systems design and development now involves looking more closely at how humans interact, communicate and make decisions. The goal is to teach computers, machines, robots, and the Internet of Things (IoT) to better comprehend, communicate, and safely interact with humans. This field of study is currently being referred to as Robot Ethics or AI Machine Ethics.

It’s interesting to note that Robot Ethics, also referred to as RoboEthics, covers both (1) the issue of moral behavior humans need to design and build into robots and AI systems interacting with humans, in addition to (2) the moral obligations of society towards its robots and ‘smart’machines. These ‘robot rights’ may include the right to life and liberty, freedom of thought, expression, and equality before the law – similar to human and animal rights.

'Deep learning' is the is one of the current terms used to describe the process of teaching artificial intelligent (AI) systems and self-learning autonomous robots to understand and solve problems by themselves, rather than having engineers having to code each and every decision or solution these non-human systems will make.

RoboEthics will be a key issue that needs to be addressed in Health 4.0 Systems.

Recent Articles on Robots, AI and Ethics

The following are a selection of recent articles on the topic of Robots, AI and Ethics that you may want to quickly scan as you delve deeper into the topic at hand:


Isaac Asimov’s “Three Laws of Robotics
  • A robot may not injure a human being or, through inaction, allow a human being to come to harm.
  • A robot must obey orders given it by human beings, except where such orders would conflict with the First Law.
  • A robot must protect its own existence as long as such protection does not conflict with the First or Second Law.
  • Robotics: Ethics of Artificial Intelligence Development of Lethal Autonomous Weapons Systems (LAWS) may be deployed within a few years - and the stakes are high. LAWS will have the ability to select and engage human targets without human intervention. Think about this!

  • Scholars Delve Deeper into the Ethics Of Artificial Intelligence - The U.S. Constitution says that every person should benefit from equal protection under the law. However, our Founding Fathers never contemplated that a ‘person’ would include an artificial intelligent robot.

  • Researchers establish a Standard for Robotic Ethics - As AI continues its rapid advances, it’s become clearer and clearer that we are dealing with some of the most dangerous technology we’ve ever developed.

  • How Tech Giants Are Devising Real Ethics for Artificial Intelligence - Five of the world’s largest tech companies are trying to create a standard of ethics around the creation of artificial intelligence. The importance of the industry effort is underscored in a recent report issued by a Stanford University group.

  • Can Artificial Intelligence Be Ethical? - It is one thing to unleash AI in the context of a game with specific rules and a clear goal; it is something very different to release self-learning AI into the real world, where the unpredictability of the environment may reveal decision-making software errors that have potentially disastrous consequences. Witness the Microsoft chat-bot called ‘Tay’.

  • Will Robots Need Their Own Ethics? - If we view robots as potential agents or persons, with a degree of autonomy that approaches or may even exceed human autonomy, then ‘robot ethics’ depends upon the notion that robots might in some sense be moral agents in their own right.

  • The Ethics of Artificial Intelligence: A Future Dilemma with Humanoid Robotics - Inverse Reinforcement Learning (IRL) allows sensor-based AI systems to observe humans, identify behaviors, which can then be converted into a form of operating system software code. This can then be used to develop ‘humanoid’ robotic systems that attempt to act like a human under most conditions. In other words, we’re turning human behavioral patterns into a programmable algorithm - the Algorithm of Life.

  • BSI's First Robot Code of Ethics Bans AI from Harming Humans - The British Standards Institute (BSI), UK’s leading business standards organization, has published a guide that outlines how robots and robotic systems should take ethics into account. 

  • Artificial Intelligence Will Radically Redesign Healthcare -  AI in healthcare and medicine could organize patient routes or treatment plans better, and also provide physicians with literally all the information they need to make better decisions.

Conclusions and Recommendations

The following are a number of preliminary observations, conclusions, and recommendations for those working on the issue of embedding ethical rules into tomorrow’s self-learning autonomous robots and artificial intelligence (AI) systems:

  • Open’ Solutions: Because Artificial Intelligence (AI) will have such a profound effect on humanity, it is recommended that AI developers have an ethical obligation to be open and transparent in their efforts. For example, check out the existing OpenCog, Open RoboEthics, and OpenAI initiatives aimed at developing ‘open source’ AI systems for humanity.
  • Software DevelopmentSoftware development teams attempting to build ‘ethical' AI and robotic systems in healthcare must be composed not only of Subject Matter Experts (SMA), systems analysts and programmers, but should also include Ethicists and Auditors specifically trained to carefully monitor the ongoing, changing behavior of autonomous self-learning robotic systems.
  • Domestic Legal Issues - With the lightening-fast development of robotics engineering and AI systems, the legal world is already way behind the curve. Congress needs to ensure a national oversight group becomes more proactive in developing laws to protect citizens before industry releases potential harmful systems on an unsuspecting public.
  • International Law - Next-generation self-learning robotic weapon systems will have the ability to make their own logical decisions on who to kill. Unfortunately, many governments around the world are already funding Lethal Autonomous Weapon Systems (LAWS) without taking appropriate precautions to protect humans from AI systems that may go ‘rogue’.

What other conclusions and recommendations do you think need to be highlighted?






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Wednesday, November 23, 2016

Local Clarendon County HS Football Team Final Scores and Schedules - November 22, 2016

As the season wraps up, the following are the final Scores and Win-Loss records for all the local Clarendon County high school football team games that were played as of November 22, 2016:
  • Manning HS Monarchs (7-4) lost to Georgetown 26-14.
  • Summerton's Scotts Branch Eagles (6-6) lost to Hemingway 20-0.
  • Clarendon Hall Saints (2-7) lost to Richard Winn Academy 34-6.
  • Laurence Manning Academy (LMA) Swampcats (7-4) lost to Porter Gaud 14-6.
  • East Clarendon HS Wolverines (1-10) lost to Cross 66-0.
The following are links to the 2016 Football schedule, roster, and detailed stats for local high schools in Summerton and across Clarendon County, SC:
* Check out MAXPREPS, a CBSSports.com web site for football team standings, other sports teams at your school, and more detailed statistics.

Saturday, November 12, 2016

Local Clarendon County HS Football Team Scores and Schedules - November 11, 2016

As the season winds down, the following are the latest Scores and Win-Loss records for all the local Clarendon County high school football team games that were played as of November 11, 2016:

  • Manning HS Monarchs (7-3) lost to Timberland 28-27.
  • Summerton's Scotts Branch Eagles (6-5) beat Bethune Bowman 38-36.
  • Clarendon Hall Saints (2-7) lost to Richard Winn Academy 34-6.
  • Laurence Manning Academy (LMA) Swampcats (7-4) lost to Porter Gaud 14-6.
  • East Clarendon HS Wolverines (1-9) lost to Green Sea 18-2.

The following are links to the 2016 Football schedule, roster, and detailed stats for local high schools in Summerton and across Clarendon County, SC:


* Check out MAXPREPS, a CBSSports.com web site for football team standings, other sports teams at your school, and more detailed statistics.

Friday, November 11, 2016

Update on Artificial Intelligence and Healthcare

The sheer volume of available medical knowledge has long since outstripped even the most capable clinician's ability to review and properly analyze the all the data now being generated and collected about a patient's health. Today it requires the assistance of sophisticated computer systems to not only help them with the analysis of the data, but to also stay on top of breakthroughs in genomics, predictive analytics, clinical decision support, population health management, and the continuous changes in best practices. Read How Healthcare Can Prep for Artificial Intelligence.

Even the best, most attentive health care providers simply can’t stay on top of all the data and the growing body of ever-changing medical knowledge. Doctors just can't be there for a patient around the clock, to catch every bad habit or reinforce every positive behavior. However, Artificial intelligence (AI) has evolved to the point that it can now begin to significantly augment the healthcare provided by physicians, pharmacists, nurses, and health coaches – not to mention self care.

Today, over 90 Artificial Intelligence (AI) startup comanies are already active in developing new solutions in the areas of Imaging & Diagnostics, Drug Discovery, Remote Patient Monitoring, Hospital Management, Customer Service, Healthcare Analytics & Research, Patient Alerts & Reminders, Telemedicine, Public Health, and more. See Artificial Intelligence Startups in Healthcare by CB Insights.

Selected Quotes
  • In a recent interview, AthenaHealth CEO Jonathan Bush noted the limitations of traditional doctors and said, “The human is wrong so freaking often, it’s a massacre.”
  • “By 2025, AI systems could be involved in everything from population health management, to digital avatars capable of answering specific patient queries.” — Frost & Sullivan.
  • Stephen Hawking has said the development of full Artificial Intelligence (AI) could spell the end of the human race – and Elon Musk agreed.


Current Examples of AI in Healthcare

Aside from the big players like IBM and Google, some of the other major startup companies focused on AI in healthcare include: Ayasdi, Babylon Health, Digital Reasoning, Gauss Surgical, H2O AI, iCarbonX, Lumiata, Pathway Genomics, Stratified Medical, Welltok and Zephyr Health – to name just a few.

The following are specific examples of major AI systems and project activities in healthcare that you might want to explore further:
  • Google Deepmind Health project is being used to mine the data of electronic medical records (EMR) in order to provide better and faster health services. 
  • Medical Sieve, an ambitious long-term exploratory project by IBM is being used to build a next generation “cognitive assistant” with analytical, reasoning capabilities and a wide range of clinical knowledge to assist in clinical decision making in radiology and cardiology. 
  • IBM has also launched Watson for Oncology that is able to provide clinicians with better evidence-based treatment options.  
  • Babylon Health has launched an app this year which offers medical AI consultation based on personal medical history and common medical knowledge. 
  • Medical start-up SenseLy uses AI and machine learning to support patients with chronic conditions in-between doctor’s visits using Molly, the world's first virtual nurse.
  • Deep Genomics aims at identifying patterns in huge data sets of genetic information and medical records, looking for mutations and linkages to disease. 
  • Human Longevity offers patients complete genome sequencing coupled with full body scan and very detailed medical check-up to help spot cancer or vascular diseases in their very early stage.  
  • Baidu has introduced an artificial intelligence-powered chatbot called Melody to connect with patients, field medical questions, and suggest diagnoses to doctors. It is a new feature of the Baidu Doctor app it launched last year. 
  • Mount Sinai Health System has tapped CloudMedx to help pinpoint people at risk of congestive heart failure as part of its emerging program dubbed HealthPromise.  
  • The Computerized Patient Record System (CPRS) developed and implemented by the Veterans Health Administration (VHA) contains a number of modules that use first generation AI capabilities, e.g. Clinical Alerts, Clinical Reminders. 
  • Open AI is a non-profit AI research company that aims to collaboratively develop and promote carefully an open source AI platform and software to benefit humanity as a whole. 
  • VA Collaborating with Flow Health to Bring AI and Precision Medicine to Veterans. Flow Health has formed a five-year partnership with the US Department of Veterans Affairs (VA) to build a medical knowledge graph with deep learning to inform medical decision-making and train artificial intelligence (AI) to personalize care plans.

AI Market & Financial Investment

According to a recent 2016 report by Frost & Sullivan, use of AI is growing in healthcare, with the market poised to reach $6 billion by 2021, up from $600 million in 2014. Cognitive solutions such as IBM’s Watson system are capable of sifting through huge volumes of data and providing guidance and decision support to healthcare providers, thereby improving work flow and patient care.

IBM is serious about bringing Watson into the healthcare industry. To build Watson’s medical credibility, IBM has spent $4 billion dollars purchasing companies that had huge stores of medical data, from billing records to MRI images. Read IBM's Watson Recommends Same Treatment as Doctors in 99% of Cancer Cases.

Artificial Intelligence (AI) coupled with the Internet of Things (IoT) could be the answer to solve major healthcare challenges that the world is facing today. IoT can helping care to move from hospital to home in low acuity and post-operative scenarios, with wearable sensors being monitored and analyzed continuously in real time by AI systems. The number of connected IoT healthcare devices is estimated to be $2.5 trillion by 2025. For more detail, read IoT and AI: Potent combo redefining healthcare.

Key Issues

Artificial Intelligence (AI) technology already exists, and is being deployed in many other arenas, such as finance and business intelligence. But in health care, there’s a human and psychological barrier: can we trust AI with our health?

Some of the key issues that need to be addressed over the coming decade before Artificial Intelligence (AI) systems are widely deployed include:
  • Ethics - This emerging issue is concerned with the moral behavior being programmed by humans into robots and other 'smart' AI systems, e.g. Roboethics.
  • Privacy & SecurityWhen AI systems are turned loose to monitor health information systems gathering data on all facets of your personal health, concerns about who has access to the data and who it is being shared with are just a few of the issues that must be adequately addressed upfront.
  • Jobs - The Bank of England has predicted that intelligent machines might take over 80 million American and 15 million British jobs, respectively over the next 10 to 20 years. The healthcare industry will not be immune to this change.
  • Legal Issues - One of the most important points of interest that needs to be hammered out first is the legality of these machines. When a doctor's gross negligence leads to a misdiagnoses and patient harm, the fault is placed squarely on the shoulders of the offending physician. What happens if an AI system were to misdiagnose a patient? Who's to blame?
  • Open Source - Many new 'open source' tools are arriving that can now run on affordable hardware and allow individuals and small organizations to perform prodigious data crunching and predictive tasks. Read about H2O, OpenAI, and other machine learning and AI tools being used in healthcare at Open Health News.

Conclusions & Next Steps

When and how artificial intelligence (AI) systems will stand in for doctors, nurses, therapists, or specialists is yet to be determined. The use of AI systems is already fairly prolific in some other industries. But the consensus is that these systems aren’t yet sophisticated enough for use in healthcare. However, expect all major electronic health record (EHR) systems of the future to include an AI platform within their architectural structure.

At this stage, AI is perceived as one of a group of emerging technologies that will increasingly be used to augment human capabilities. However, within 10 years AI coupled with IoT, Blockchain technology, and 'Big Data' Analytics may actually be used to carry out many of the functions currently being performed by clinicians. Read Making Us Better At The Things We Do Best.

As we continue to move forward with further development and deployment of AI systems, the following are some of the next steps that need to be taken:
  • Ethical rules and standards to be incorporated in AI systems used in the healthcare need to be extensively addressed.
  • The health IT industry needs to take careful, incremental steps when developing and implementing AI systems in healthcare over the next decade to avoid causing any harm.
  • Medical professionals need to become much more knowledgable about AI technology and systems and work closely with developers before we move forward much further.
  • Patients need to get accustomed to interacting with AI systems, discovering the potential benefits to themselves – to trust these new systems.
  • Companies developing AI healthcare solutions need to carefully communicate with the general public about the potential advantages and risks associated with the use of AI in medicine.
  • Healthcare oversight institutions need to carefully measure the success, shortcomings, and effectiveness of AI systems before they are widely deployed over the coming decades.

The next few decades are going to be an exciting time in healthcare. You might want to take a few minutes to read Searching for Godot – Health 4.0 by 2040.


Selected Links