Ecosystems and Personal Healthcare

To reach a stage where healthcare will be personal, there is a fundamental step: designing a medical treatment considering individual variability. For such purpose it is necessary to combine and curate to existing EMR records with data about the patient’s societal environment, lifestyle, and their genomic data. This can assist the doctors in identifying which approaches, treatments, and preventions will be effective for the patients, what also can be called personalized healthcare, on the prevention side, would also allow identification of genetic variants that increase a patient’s chances of developing diseases. Treatment could begin earlier, helping reduce risk through behavior modification (healthier diet or increased exercise) or leading to placement of patients on drug therapies.

Such an outcome relies of connecting and sharing data within a particular ecosystem. The ecosystem of me (ties back to the earlier concept of the internet of me). On one hand phone, wearables, health sensors, connected clothing—and combining that with clinical tests, scans, and check-ups—will allow much-improved analysis and monitoring and focus on health optimization. On the other hand, sharing such data in medical doctor community, academia, healthcare think tanks will improve healthcare foresight and shape healthcare public policy design, but most importantly will support via the existence of such dataset to create models of detecting effectively symptoms, understating treatment impact, find new ways of treatment and assist medical doctors with assisted reasoning.

 

Personalized healthcare is about shifting from volume to value. Revealing the unknown and creating a healthcare ecosystem continuum. The purpose of the transformation journey is to shift from normalized healthcare to personalized healthcare.

 

1

Personal Healthcare Ecosystem

 

With this type of engagement, patients are likely to be more cooperative, and comply with procedures and treatment plans. There are of course other kind of benefits, like ease to schedule an appointment and track medication time, decrease healthcare costs, however, the biggest benefit and value of such an approach allows patients and citizens to look after themselves better and have better quality of life, because healthcare become, personal, anchored on a personal health record, which data sharing consent is managed by the individual.

Technology and healthcare always had an uneasy relationship, and the latest announcements that Apple and Google did entering into healthcare may bring the argument of massive surveillance, however, countries like Singapore, are aggressively progressing towards the creation of a shared nationwide healthcare data lake, by law. It should give us some thoughts about how healthcare is fast becoming personal.

The Man and the Machine and the impact on the Future of Work

Many people wonder the reasoning of Microsoft’s [1] mission which is: “Empower every person and every organization on the planet to achieve more” . It can sound a cliché, but I could never be more important to reinforce the message, once we are coming out of repetitive work and normalization of processes, which are step by step being totally automated – by the use of technologies like robotic process automation – shifting to the knowledge work space.
I’ve seen based on my experience working with Oil & Gas companies, that the idea of an industry that monolithically crystalized is not a reality anymore. This type of industry sector is being enabled by a set of technologies that took time to mature, combined with challenges related with network infrastructure availability and latency (oil production occur in remote areas of in the middle of the ocean where connectivity is a scarce resource), but today are becoming mainstream. For example using drones to make inspections, mixed reality for executing field inspections, collaboration remotely with engineers in the control center or using cameras for detecting safety (lack of protection equipment) or security (facility intrusion) with image pattern recognition. These new technologies  are also creating a job and career change  widened by the adoption of new technologies and talent scarcity. Two reports from World Economic Forum, named, Towards a Reskilling Revolution and Future of Jobs, highlight:
Companies, “expect to hire wholly new permanent staff already possessing skills relevant to new technologies; seek to automate the work tasks concerned completely; and retrain existing employees. The likelihood of hiring new permanent staff with relevant skills is nearly twice the likelihood of strategic redundancies of staff lagging behind in new skills adoption. However, nearly a quarter of companies are undecided or unlikely to pursue the retraining of existing employees, and two-thirds expect workers to adapt and pick up skills in the course of their changing jobs. Between one-half and two-thirds are likely to turn to external contractors, temporary staff and freelancers to address their skills gaps.”

I was invited as a speaker to the Halliburton Life conference in Abu Dhabi. One of the trends I noticed – as part of the reinforcement on how intrusive artificial intelligence is enabling a new set of possibilities, like for example, improving decision making in terms of financial impact while making seismic data interpretation in terms of addressing exploration and production viability – is how hard is for individuals with strong domain expertise to work. I heard during sessions people expressing frustration on manipulation data sets, being not able to work of the same updated version of a data set, becoming unproductive waiting weeks for results and deal with uncertainty.

I am having a series of meetings with HR function and I’ve been told that the way people work is becoming frustrating and unproductive, despite all ubiquity of cloud, social, bring your own software / device or putting into a different perspective, it is not achieving the expected results. There was definitively productivity improvements, mostly in terms of mobility, meaning individuals can work anywhere at their pace, have access to information they commonly use on every day. However, mirroring self-expression, self-development (be digital ready), achieving a true networked work environment – far from being reached, companies with workforce size higher than 5.000 individuals find how difficult it is to reach out experts, knowing what is happening across domain of expertise which people operate, be part of working groups to construct new identities to replace old ones, avoiding to become redundant as a way of personal fulfilment – and ultimately, how technology ubiquity is bringing lack of integration, distraction shifting our attention on meaningful activities. As an example, people envision a future which individuals participate in a meeting, don’t need to search for meeting content in “teams workspace”, don’t need to connect to a projector, don’t need to write meeting notes, spark and track action items.

Studies carried in an Oil & Gas major using Microsoft’s workplace analytics reveal that in an investment venture appraisal that took 1 year to complete, more than 2.000 individuals were involved with a strong presence of financial departments. As a result, this contributes to:
  • Slow decision making and limited agility;
  • Employees being over-managed;
  • It was possible to gain more than 300 FTEs worth of time by rethinking how work and management is distributed;
  • Cross-functional processes becoming bloated and expensive.
People aspire a future which individuals participate in a meeting, don’t need to search for meeting content in “teams workspace”, don’t need to connect to a projector, don’t need to write meeting notes, spark and track action items. This is not a futurist idea. This a desirable outcome.

 

3 pillars of Human Led Design
To address this, it is necessary to rethink how technology should pursue a human led design strategy:

  • Help people achieve what is important to them. This something that during all the years companies have worked in operational improvement did not fully deliver. For example, can’t we let people organize and define their own User Interface in a way they will focus on what is really most important to them?
  • Building relationships. There is an intense debate on methods to discover how to get to know individuals and understand their real needs and wants based on trust, re-quoting Elizabeth Tunstall that provides an interesting perspective, as our universal individuality is cannot separated by the sacred, profane and spirituality, instead of creating personas framed on a stereotypes which we must be forced to fit.
  • Design technology that seamlessly integrates into the human world. Design for the capabilities and limitations of the human body. Adjust to the human needs dictated by the physical conditions of an environment or device. For example, designing an application to be operated in an explosive and noisy environment is different for designing the same solution to be operated in a control center.
Future of Work scenarios
The future of work is deeply related with employee upskilling and retainment. Being able to make the change in terms of employee experience will contribute to retain talent for next generation of workers.
Below is a spectrum of possible scenarios to explore in terms of what the future of work can be.
Some are more easy to productize, other’s, like augmented knowledge reasoning aren’t, but it is still worth trying – I remember previous engagements related with public policy enactment as an example – i.e. government agency wants to increase taxes and wants to recommend a scenario that is going to maximize tax collection and minimize negative population sentiment, using A.I. for that purpose.
Annotation

Collection of Future of Work Scenarios

In summary, guiding principle is focusing less on jobs descriptions and more on the nature of the work produced and then determining how to help employees accomplish those tasks enabled by scenarios like these:
  • Digital assistants may include a digital shadow that will observe behaviors, build and maintain work preference rules, search information, predict and remind you about important actions to accomplish based on the nature of the work you are working on.
  • Unified interactions allows employees to take actions on tasks, gain access to the data feeds they follow, collaborate with other individuals, all without ever leaving a single customized interface according his needs and wants, instead of jump from application to application.
  • Digital upskilling is about training the workforce, with content hyper-personalization based on a role definition execution requisites and performance review feedback. In a world that is becoming digital, the workforce is must be digital ready instead of digital impaired.
  • Collaboration (at large) as a digital extension of individuals senses, contextual knowledge support it serves as an interface for humans to the physical world. Enhance the user’s surroundings with relevant, and/or actionable information, using as an example, mixed reality to augment our ability to perform.
  • Reasoning leveraged on recommendation agents based on past interactions and other sources of information to jump-start and kick-off knowledge-oriented activities. Incorporate specialized Artificial Intelligence technologies processing functions tuned specifically to answer questions, create models, to support decision making.

You can’t optimize for everyone, but it is worth making a profound change happen in our working habits this will help organizations that they cannot digitally transform unless people do.

[1] I am Microsoft employee when this post was written.

 

The man and the machine manifesto – Part II

 

In the man and the machine original ramblings, I alluded to the to the discerning challenge between humans and powered Artificial Intelligence machines will work together, against the “tangled recursion” [14] as an example of machine intelligence. This log entry expands deeper the doubts and wonders about man and machine co-existence.

Cybernetics the need of adopting other forms of intelligence

Cybernetics become popular when the works of the first generation of cyberneticians like Norbert Wiener and Ross Ashby grow reputation from the lectures of Stafford Beer [10] and the works of Gordon Pask on training and teaching machines [11]. Applying the laws and principles of cybernetics, especially the law of requisite variety – control can be obtained only if the variety of the controller is at least as great as the variety of the situation to be controlled [8] – to the design of effective organizations, Stafford Beer formulated the Viable System Model (VSM) [9] as a method for designing organizations that are able to survive and thrive in a changing environment [9]. The VSM was then a vision of the organization in the image of the human species. Functions of management and control were envisioned on the lines of the human brain and nervous system. The brain and nervous system, were simulated by a combination of information technologies and human interaction. The VSM is probably one of the most elaborated representations of the fusion of the man and the machine [12] and the primacy of the role played by information in control systems and decision making. The fusion or combination of man-machine can be considered in form as a cyborg – that has certain physiological and intellectual processes aided or controlled by mechanical, electronic, or computational devices [13].

The limitations or the utopia of singularity

 

 

The achievement of singularity is perceived or motivated by advocators that show fear of death or want to reach a stage of immortality and therefore are irrational, combined with the fact of the looming of the ubiquitous computing, which, computing is made to appear everywhere and anywhere [6] with possible endless workloads combinations, omnipresent, making computing an embedded, invisible part of today’s life. Singularity is perpetually 15 to 25 years in the near future and that future keep being delayed [5]. Singularity supporters, tend to forget about the computing limitations on some of the use cases that are just about to become a reality, like for example, brain simulation. To simulate 10 seconds of real brain time would require about one year of computer simulation [7] in the current most powerful existing supercomputer.

Do we want machines to feel or do we foster a future which humans will augment their natural born capabilities?

 

 

Feelings can only be won by creatures who already have a mind and you can only have a mind if you have a nervous system [1], which in the case of machines, is absent. In the past decade, there an intense debate about if machines can or will feel. Emotions are considered as a non-detachable part of intelligence. Emotions be catalogued as rage, fear, panic, love, happiness and it can drive to take actions. Humans classify emotions and assign them some other emotional value [2]. Such value changes taking into consideration the societal environment humans live or are surrounded by. What can be condemned in one society can be accepted in other. The meaning of the the emotional values is the basis for conscious experience. Therefore, understanding the cartography of the interaction the human and the environment is critical for understanding the nature of consciousness [2]. Our universal individuality is cannot separated by the sacred, profane and spirituality [3]. The flow of other people, nature, environment and ancestor influence that provided us the life principle guidelines we adopt or tend to ignore that is a consequence of what surround us and make us unique individuals. Because machines do not and most likely will not possess consciousness, they are incapable of having free will and intentionality, something that is an essential criteria for moral agency [4].

 

References:

[1] António Damásio – In The Strange Order of Things: Life, Feeling, and the Making of Cultures – ISBN – 9780307908759

[2] Mark Solms – The Brain and the Inner World: An Introduction to the Neuroscience of the Subjective Experience – ISBN – 9781590510179

[3] Elizabeth Tunstall – Decolonizing Design Innovation: Design Anthropology, Critical Anthropology and Indigenous Knowledge in Design Anthropology Theory and Practice – ISBN – 9780857853691

[4] Kenneth Einar Himma – Artificial agency, consciousness, and the criteria for moral agency: What properties must an artificial agent have to be a moral agent?. Ethics and Information Technology, 11(1), 19–29 – ISSN: 13881957

[5] Stuart Armstrong, Kaj Sotala – How We’re Predicting AI or Failing To – In Beyond AI: Artificial Dreams, edited by Jan Romportl, PavelIrcing, Eva Zackova, Michal Polak, and Radek Schuster, 52–75. Pilsen: University of West Bohemia.

[6] Dietmar Möller – Guide to Computing Fundamentals in Cyber-Physical Systems Concepts, Design Methods, and Applications – ISBN – 9783319251769

[7] Arlindo Oliveira – The Digital Mind: How Science is Redefining Humanity – ISBN – 9780262036030

[8] W. R. Ashby, An introduction to cybernetics – ISBN – 9781614277651

[9] Stafford Beer, Brain of the Firm – The Managerial Cybernetics of Organization – ISBN – 9780471948391

[10] Roger Harnden and Allenna Leonard – How Many Grapes Went into the Wine: Stafford Beer on the Art and Science of Holistic Management – ISBN – 978-0471942962

[11] Andrew Pickering – The Cybernetic Brain: Sketches of Another Future – ISBN – 9780226667904

[12] Stafford Beer – Diagnosing the systems for organizations – ISBN – 9780471951360

[13] Woodrow Barfield – Cyber-Humans – Our Future with Machines – ISBN – 9783319250489

[14] Gödel, Escher, Bach: An Eternal Golden Braid – ISBN – 9780465026562

 

The man and the machine manifesto

“Self-organised systems, lie all around us. There are quagmires, the fish in the sea, or intractable systems like clouds. Surely, we can make these work things out for us, act as our control mechanisms, perhaps most important of all, we can couple these seemingly uncontrollable entities together so that they can control each other. Why not, for example, couple the traffic chaos in Chicago to the traffic chaos in New York in order to obtain an acceptably self-organising whole? Why not associate brains to achieve a group intelligence?”

Gordon Pask, The natural history of networks

 

Today there is a shadow or sense of doubt if we as humans want machines to think or to do – some people already argue they do think, detached from the consciousness bond – and it would replace humanity soon, as many others advocate singularity is near with systems that can adapt themselves, command, control other systems, something as Douglas Hofstadter referred to “tangled recursion” as an example of machine intelligence.
I ultimately believe that humans and powered AI machines will work together, not compete against each other. Humans will be much more empowered by the symbiotic combination of machine work, meaning that we will need to continuous to adapt to rather than become indispensables, we increase our own capabilities.
However, there are many untamed challenges in terms of such man and machine symbiosis, as we the human species, have the responsibility to define by which rules we want to live, as machines progress in new areas, changing the foundations on our society is organized, as per bellow.

Governance
Much has been discussed how to define machine design rules and relevant regulation. Some experts believe that is the hands of humans to define such rules and while machines are tightly controlled by humans we can define how machines should be engineered. However, some examples related with war machines, demonstrate that Isaac Asimov’s laws do not apply anymore, once the potential for harm is increasing rapidly.
Hence the challenge stands. Consider the scenario of an intelligent medical system that provides counselling and advisory, induces a medical doctor with error. Who is responsible? The Doctor? The system? The entity that conceived the system? The trainer that trained the system to make decisions, based on a knowledge base? How do we deal with human life loss? Regulatory bodies for the engineering profession or other domain expertise, have clearly defined rules for design or professional act decisions, made by humans, however, in terms of machines endowed with any kind of intelligence, governance appears missing and there is no common broad agreement.

Societal impact, innovation and economy growth
There is no doubt that technology was always the common denominator that sparked economic growth, the press, steam engines and lastly the internet, created in three different moments in time tectonic shifts. However, prosperity also contributes to unemployment. Technology tends to automate at scale and replace repetitive tasks, but the last wave of technological developments is already targeting knowledge workers as well. Hence, the challenge is not related with low income workers only. The balancing act should be how the use of technology can contribute to higher living standards, diminish inequality and drive inclusion.

Human and Machine Interface
Mixed reality is becoming a popular interface in human-computer interaction for combining virtual and real-world environments, and it has recently been a common technique for human-robot interaction, it price is however a barrier for adoption and creates digital imparity. Natural language processing is becoming another de-facto interface, applied for example on business to consumer interactions, but some questions are still not addressed in terms of humans that speak a language blending influence of their own culture that a machine is not aware of. Despite the advance interacting with devices like smartphones, as technology progresses, it is relevant do involve interface designers to make a reflection how machines affect human to human interactions and human to machine interactions.

Ethics
Tackling the trade-off between privacy and security is today already a challenge, related to the fundamental but complex separation between what constitutes the private and the public space of an individual. The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in another can be condemned. The concept of privacy is constantly being redefined to a point that can be transform into a matter of transparency, for example, sharing publicly your taxes declarations if you are a politician. How we deal with ethics in terms of a machine that have access and share our medical records that will make decisions in terms of triage or sense of urgency related with medical treatment? It’s in ethical that a machine can make judgment about predicting future crimes or provide a credit risk score based on data that is related with our profiles?

Would you consider ethical to create a system that reproduces an nonexistence life form in other medium?

Wired published a story about a son that knew that he was just about to lose his father and created a BOT, called DadBot, to preserve his existence. The story can be found here.

As I finished reading the article two, above many other questions came to my mind:

  1. It is ethical to preserve the existence of a living being after his death? The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in another can be condemned. Now, I believe because this is a foundational universe functioning rule, that what is born it will die. We all know that we want to preserve the life of our beloved ones and definitively there are scientific studies that demonstrate how positive it is to create other ways of engagement with a person that does not inhabit our world. However, is my belief that recognizing that someone died, implies we cannot recreate interaction. One can argue that browse pictures or watch videos is another way of interacting. Would you consider ethical to create a system that reproduces an nonexistence life form in other medium?
  2. How fast the system is going to become obsolete? James Vlhaos, refers that he collected information from his father in a way that the BOT could later share stories and past experiences with the interlocutor. He provides an example how the system is context aware and interacts with the user remembering past stories that were lived together, “Remember that big barbecue dinner they hosted for us at the taverna?” – he writes – nevertheless, what happens when there are no more stories to tell? Are we interested in repeat the experience until exhaustion is reached? One can argue that is the precise function of the system and immortality is reached. If you want to know about a person, particularly younger generations that never met that person, they can get acquainted without facing the risk of facts distortion or even loss, as it happens when the elder generations die and the memories are washed away with the dead. On the other hand, this is another way to preserve the bond, the ties and the affection, like it happens in real life and people like to repeat the same stories over and over to create that sense of collective existence. Last, how do you as a solution architect, a designer, choose the content? Image that your relative committed war crimes, something that second world war generations need to deal with in Germany, would you recreate the life of your siblings, your grandfather if you knew he committed such crimes, would you hide those facts or would you expose it?

BPM Conference Portugal 2017 – Agenda Synopsis

Artificial Intelligence (A.I.) is for the time being and important new domain to be discussed. As far I am concerned, perhaps the most productive debate we can have at the conference in the 2017 edition isn’t the one of good versus evil, the rise of the machines or singularity is near. The debate could be about the guidelines instilled in the people and organizations using A.I., something that cybernetics tried to push back in the 60’s.

Why the human element still matters?
While demand for efficient, transactional, prediction-driven workplace systems is on the rise, just look around you and you will realize that most of the interactions you have with companies or even to perform daily tasks – like find the better route to commute – have embedded intelligence and are context aware, taking into consideration your location, profile and transactional history. However, there are a set of skills we seemingly don’t want systems to perform. Despite new techniques like deep learning are denting our ability to prevent we will become dispensable, emotional intelligence is said to be among the fastest-growing job skills, and some experts say the ability to collaborate and listen thoughtfully can even protect your position and help advance your career over the next decade as automation progresses. This is probably the reason that contact centers were not totally replaced by robots. Yet.

Ultimately, humans and machines will work together, not against one another. This is already a reality. Imagine if human and machine work together to solve society’s greatest challenges like providing healthcare services, probably one of the areas on which we have seen the deepest progress, as well as, fighting insurgency and keep our cities safe. As machines become more intelligent, they become more capable and we can rely for daily or even knowledge intensive tasks. Businesses of all industry verticals will benefit from these new systems of intelligence machines that can better detect image patterns, process natural language and make informed decisions. This is the reason why you attend Paul Harmon session. Paul is a legend in Business Process Management, probably is one of the best domain knowledge experts I ever came across. His experience is legendary and he will focus about the looming of AI in a multitude of industry sectors, as well as what it means in terms of process design and execution.

For many business, the new spectrum of possibilities provides not just an opportunity to automate processes and become more efficient, but to fundamentally change business models under the new digital transformation moto. Many of today’s advances breakthroughs can be attributed to evolution in machine learning. Machine Learning, is being used across many industry sectors, like Financials and Healthcare.  This kind of supervised learning means that we can convert data into intelligence in the sense that these networks can look for patterns or features in the data they are given. Paulo Cortez is going to talk about how AI can be used to extend our life expectancy, by predicting human organ failure or real examples on prescription marking in Financials, also known as next best action, a technique that induces spending on financials products based on real customer needs and desires.

Now is the time for greater coordination and collaboration on A.I. New kinds of services such as personal digital assistants, chat bots and so on are also defining new ways of interacting with humans. However, we simply don’t want to chat to a smartphone. We need a sense of friendliness that can enhance customer’s perceptions of the company. Bianca Fortuna is going to talk about a convergence of several technologies to make some extraordinary advances in terms of operation management.

For businesses, the new possibilities provide not just an opportunity to automate processes and become more efficient, but to fundamentally change the way they operate. Ross Brown, is in my opinion, one of the most prominent researchers in terms of process simulation, optimization in virtual worlds. When everybody was still stick to simulation tools, Ross was leading the way using new concepts like 3D simulation and today he is applying mixed reality approaches to explore the next frontier in terms of process optimization.

A.I. must be designed to assist humanity. I firmly believe on it. As we build more autonomous machines, we need to respect human autonomy. Collaborative robots, or co-bots, should do dangerous work like operating in hazardous environments, creating a safety wall and safeguarding human life, combined with vital sign monitoring to prevent human life loss. We are now at the tipping point where we are seeing a convergence of several technologies, robots included that jumped from the factory floor to the office space. That is the reason of the relevance of Manuela Veloso talk and how we can co-work together with robots.

I am looking forward to see you at the conference.

BPM Conference Portugal 2017 – Artificial Intelligence

BPM Conference Portugal 2017 is going to talk about artificial intelligence.

Artificial Intelligence (A.I.) is for the time being and important new domain to be discussed. As far I am concerned, perhaps the most productive debate we can have at the conference in the 2017 edition isn’t the one of good versus evil, the rise of the machines or singularity is near. The debate could be about the guidelines instilled in the people and organizations using A.I., something that cybernetics tried to push back in the 60’s.

Why the human element still matters?
At the same time that demand for efficient, transactional, prediction-driven workplace systems is on the rise, just look around you and you will realize that most of the interactions you have with companies or even to perform daily tasks – like find the better route to commute – have embedded intelligence and are context aware, taking into consideration your location, profile and transactional history. However, there are a set of skills we seemingly don’t want systems to perform. Despite new techniques like deep learning are denting our ability to prevent we will become dispensable, emotional intelligence is said to be among the fastest-growing job skills, and some experts say the ability to collaborate and listen thoughtfully can even protect your position and help advance your career over the next decade as automation progresses. This is probably the reason that contact centers were not totally replaced by robots. Yet.

Ultimately, humans and machines will work together, not against one another. This is already a reality. Imagine if human and machine work together to solve society’s greatest challenges like providing healthcare services, probably one of the areas on which we have seen the deepest progress, as well as, fighting insurgency and keep our cities safe. Other area that is being disrupted is transportation. Some car manufacturing companies are already assuming that in the future most of the people will not own a vehicle and autonomous commute will be a de facto-standard in high density population areas.
This is probably one of the most sensitive areas of discussion, but we will see that today we can do much better humans if we combine our work together with A.I. systems.
How to enforce principles in the design of A.I. systems?
I would argue that perhaps the most productive debate we can have isn’t one of good versus evil. The debate should be about the values instilled in the people and institutions creating this technology. We must enforce technology with protections for privacy, transparency, and security. A.I. must be designed to detect new threats and devise appropriate protection and must be inclusive and respectful to the human being. This put an extra challenge –  more than discussing on rules, policies and how to implemented coding, is the foundation principle on what is right and what is wrong. The definition of a concept, a domain, is a consequence of the surroundings, of the environment we live and the multitude of human principles and beliefs. What in a society can be accepted as a practice, in other can be condemned.
If in the future A.I. can bring transparency, in what kind of transparent society we want to live? Being transparent means you are not afraid of hiding your medical records because it can save your life, as also you are not afraid of exposing your earnings and tax situation. Becoming transparent will also contribute to avoid crime, bribery, and corruption? Or being transparent is the realization of the classic Orwellian apocalypse that looms and take control of our society? Anyway, from a solution design perspective it is necessary to define the particulars about data protection and security, among others, setting-up specific rules concerning the processing of personal data in the electronic communication sector. What people most often want is a sense of control over their data (even if they don’t exercise this control very often). Many people feel that this control is a fundamental human right (thinking of personal data as an extension of the self), or an essential part of your property rights to your data.
To that end, this is something we must debate during the event.
Will A. I. power the next industrial revolution?
Advances in technology is powering the next industrial revolution, basically blurring the physical and the digitaldivide. Technology is today omnipresent. Capitalizing on this phenomenon is the key to innovation. From the rise of A.I. and related technologies, the challenge and opportunity for business leaders is to harness the ubiquitous, disruptive force of technology to be more agile, fuel efficiency and ultimately shape the shape of the industry destiny. Definitely in this next industrial revolution, we are facing a range of new technologies that combine the physical, digital and biological worlds. Failure to understand how to embrace A.I. into operations and business models, may end up of being out of market.
Having said this, should companies do a deep dive with A.I. or not?
How can we put A.I. work for the goodness of our own society?
For healthcare, A.I. can advance recommend the most effective treatments for their patients, as well as, predict human body organs failure and increase our life expectancy.
For transportation, A.I. can improve the efficiency transportation systems, integrating supply chain on real time, prevent incidents, optimize the fuel consumption and safety and support maintenance of infrastructure.
For public safety, A.I. can deploy predictive models for crime and help security forces to find associations in massive amounts of information to spot insurgency and handle complex crime cases.
For financial services, A.I. can manage must better risk exposure, by ingesting millions of data segments used in risk models, reduce fraud and tax evasion, assist in providing the best insurance coverage at the right cost combining data provided by the customer and its relationships.
For individuals, A.I. can assist humans in developing personalized recommendations based on the stage of life the individual is, combining data about the individual preferences, beliefs and transactions.
In this globalized world, economy growth crucially depends upon the creation of new business models that rewards more effective outcomes and overall benefits to society. If business model innovation was always behind differentiation and competitive advantage, A.I. is for sure a technology can enable a more innovative society.