Artificial Intelligence

Three Ways to Facilitate a Symbiotic Relationship Between Cognitive Intelligence and Behavioral Sciences

After every conference I speak at about the transformative power of Artificial Intelligence and its potential to unlock untold business value, the one question that often crops up from the audience is.. if AI is expected to perform much of the grunt work in the enterprise world, what scope is there for the so-called ‘human’ qualities?

Is the future of business and technology so deeply intertwined that it leaves virtually no scope in the future for the vagaries of human intelligence and behavior? The answer is quick and simple – absolutely not. Artificial Intelligence, while a great paradigm-shifter in the world of business, is still one of the tools that will be used by humans for making better decisions. At the end of the day, AI will still be developed and used by humans. And maintaining the ‘human element’ in the way it is made, delivered, used and improved will most certainly make it a lot more successful. AI exists to make human life simpler and richer – and hence it is critical that AI practitioners and data scientists adopt a human-centric approach to its development, deployment and adoption. Even the best AI will become quickly redundant without inputs from real humans on how to accelerate strategic decisions and processes.

How do we then build in that ‘human element’ into our Artificial Intelligence tools? This is where humanities-centric subjects of design and behavioral science come into the picture. What is behavioral science? Simply put, it is the study of internal cognitive processes of humans and societies and how these processes manifest into external perceptible and imperceptible actions and interactions. Behavioral science typically stands at a nexus of various subjects – borrowing aspects from sociology, anthropology, psychology and even economics and political science. Its interdisciplinary nature precludes the scale of impact it can have if applied correctly. In technology, and specifically in AI, behavioral science will and should impact how we build, use and interact with technology.

 

I see primarily three key areas where the symbiosis of AI-led cognitive intelligence systems and behavioral science can unlock massive value for enterprises that marry these two starkly different, but extremely complementary fields of study:

Appeal to the Non-Conscious

We have known for nearly a century now that a large majority of human biases, inferences, preferences and reactions are largely controlled by the dark recesses of our non-conscious brain. For technologists to build successful AI products, that are widely adopted and used they need to reach out inside the non-conscious parts of the human brain and orchestrate responses from there.

In AI technology specifically, user adoption is often the difference between make and break for products. Numerous AI products are mostly informed by the data they gather from human actions and their preferences. This data feeds the algorithms running in the background and makes them more sophisticated to better understand their human overlords. To that end, AI products need to have a strong underpinning in behavioral science, so that they can appeal to the non-conscious and improve adoption.

Take for example the work done by Nir Eyal for his book, ‘Hooked: How to Build Habit Forming Products.’ In the book, Eyal writes about multiple ways in which human subjects get applied to technology development. One of them is the Hook canvas – a loop comprising triggers, actions, rewards and investments – which are the cornerstone features of every addictive software you’ve used – from Facebook to Instagram, Snapchat and YouTube. Another is the idea of using the trinity of emotion, features and incentives – extremely relevant ideas to anyone working on building AI products. Another example comes from Worxogo – an Indian startup that employs behavioral design, neuroscience in tandem with predictive analytics to enhance employee performance through nudges to the non-conscious.

Build with Humans

Not only is AI built to serve humans, it is also built by humans. To that end, it becomes extremely important to consider what emotional triggers help define what we build and how we build it. Again, behavioral science practitioners have a key role to play in order to engage empathy in defining the requirements and going about the development of AI. Learnings from behavioral science can bring to light immeasurably important interventions for how we manage and lead teams, collaborate between a team and across multiple teams – all while maintaining a high level of motivation by appealing to a higher sense of purpose. It is worth examining how something as simple as empathy can be extremely valuable in how we build software. For instance, with improved self-awareness and empathy, developers can feel an intrinsic desire to write cleaner code while maintaining proper documentation. Also, given that AI is largely deployed using the DevOps methodology – empathy can be the difference between whether we can build a trust-based bridge between how we build, deploy and automate releases faster.

Beyond the ‘how’ of AI development, behavioral science can also contribute meaningfully to the ‘what’. Currently a lot of concern around AI is related to ethics – will AI lead to loss of meaningful work for humans? What data privacy issues can rear their head when we deploy large-scale data capture systems to improve our algorithms? We need to move the dial from apathy to empathy in the process of conceptualizing software – and knowledge of behavioral science will undoubtedly help AI practitioners develop more responsible AI.

Artificial Emotional Intelligence

The third key application of behavioral science – and possibly the most game-changing of the lot is – how can we apply behavioral science to make our systems more ‘human’? Is it possible to add a dash of EQ to these high IQ systems?

I certainly think there is a huge scope for developing AI that has a strong human bent. Consider the applications we are building today with AI and robotics – companions for the elderly, coaching apps for autistic children, even something as comparatively mundane is chatbots for customer service. Behavioral science holds the key to achieving the holy grail of how we can better balance the human-machine equation, by infusing human qualities into artificial systems.

To enable this, it is important to know who we are building for and what are their intrinsic and non-conscious needs. Behavioral science holds the clues that can complement AI’s ability to eliminate biases, while serving the emotional needs of humans. For example, StressSense tracks when people are highly stressed and helps them avoid anxious situations. This kind of breakthrough research can help in multiple AI applications, teaching them how to behave with humans, while ensuring a strong impact.

As technology providers and businesses work together to build transformational artificial intelligence systems and data science teams, it is very important to consider the human element. These teams would do well to develop a better understanding of whom the AI is built for and how it is used – through techniques offered by behavioral science. Balancing the human-machine equation and powering a complementary relationship between AI systems and the people who use them necessitates an infusion of behavioral science into the process. Ultimately, for AI to succeed, we need both – the foresight of technology as well as the insight of humans.

#AI & #BigData

Sameer Dhanrajani is Chief Strategy Officer at Fractal Analytics

Read Source Article Forbes

 

 

Until technology allows us to upload our consciousness to a computer when our physical bodies start irreparably failing, death is going to remain a real thing. But what if you could continue communicating with loved ones — or, at least, a reasonable facsimile of them — long after they’ve shuffled off this mortal coil? It might sound like an episode of Black Mirror (it is!), but it’s also the basis for a recently announced research project being carried out at India’s Shree Devi Institute of Technology.

Researchers Shriya Devadiga and Bhakthi Shetty have been investigating how a chatbot could be made to duplicate a person’s personality digitally, granting users the ability to chat with an A.I. approximation of an individual, such as a family member, who is no longer around.

For their study, the researchers used Replika A.I., an app created by Russian coder Euginia Kuyda. Replika trains a chatbot designed to replicate an individual’s communication patterns by using their digital conversations as training data. Through pattern matching, the more you chat to your Replika A.I. chatbot, the more its sentences sound like something that you would say. Or, in the case of Devadiga and Shetty’s proposal, something that your deceased relative, loved one or friend might say.

“Something such as this could help people to overcome their trauma after losing their beloveds”

This could be achieved by feeding it the sum total of an individual’s available social media presence, tweets, emails, and any other relevant information, to produce a virtual entity that is as close to indistinguishable from them as possible. Think of it like a Turing Test with a touch of Frankensteinthrown in for good measure.

“[Something such as this could help] people to overcome their trauma after losing their beloveds, is what this use case serves,” Shetty told Digital Trends. “In a fast growing world full of technologies — and especially a booming [field like] artificial intelligence — I think this would prove desirable. Because in such a world, nobody would like to spend most of their time depressed or mourning over their loss … Now this could be chilling, but that’s the truth.”

A research paper describing the Shree Devi Institute of Technology project was recently published in the Asian Journal of Convergence of Technology. Unfortunately, as fascinating as the concept of virtual immortality might sound, at present the project remains a hypothetical one; a peer-reviewed version of the kind of conversation a couple of stoned roboticists might have at 2 o’clock in the morning.

NOT THE ONLY EXAMPLE

This isn’t the first time that the idea has been brought up, however — with varying degrees of complexity. Given the somewhat unsettling nature of the idea, a number of companies have tried to tap into this nascent netherworld market. This ranges from efforts like Google’s Inactive Account Manager(“Make a plan for your Google Account if you pass away”) and the startup DeadSocial, which simply allow users to bequeath their data to people they trust after their death, to more fully realized attempts to use this data to do something frequently unsettling.

Read the Source Article Digital Trends

#AI #ArtificialIntelligence #chatbots 

IIT Delhi and IBM on November 29 announced that they will join IBM’s AI Horizons Network to accelerate a multi-year research on artificial intelligence (AI) technologies. The strategic alliance puts IITD into an elite group of global universities that was earlier represented by IITB as the only Indian entrant. This alliance aims to discover path-breaking AI techniques which can assist organizations to take informed decisions. The teams from IITD and IBM jointly plan to publish their research in peer-reviewed academic journals and aim to open challenges and release datasets to the research community in a bid to identify new research areas.

IBM’s AI Horizons Network

IBM’s AI Horizons Network aims to discover novel AI techniques which can help organizations take informed decisions by being able to logically reason with their AI systems.

With the announcement, IIT-Delhi becomes the second institution outside North America to join the prestigious IBM’s AI Horizons Network. This network brings the expertise of IBM Researchers, top graduate students and a world-class faculty who work together on a series of advanced research projects and experiments designed to accelerate the pace of natural language processing, artificial intelligence, machine learning and other emerging technologies.

The AI Horizons Network projects are designed to apply the evolving technologies into some of the world’s most pioneering challenges, ranging from disease, environment, cybersecurity, transportation and education. The Network addresses the unstructured and structured data concerns required to train machine learning systems in a bid to build new computing infrastructures, to optimise new data-intensive solutions for the emerging digital world.

As a part of the collaboration, IBM researchers will partner with professors and students from the Department of Computer Science and Engineering at IIT Delhi for a joint research which has the potential to benefit a multitude of sectors like Finance, Healthcare and Medicine, and Customer support which together bring complex set of questions and unstructured data into the analysis.

Valuable Collaboration to Drive Research

 With this collaboration, IIT Delhi joins the distinguished list of universities like the Massachusetts Institute of Technology, University of Illinois Urbana-Champaign, Rensselaer Polytechnic Institute, University of Michigan, and University of Maryland at Baltimore County, Universite de Montreal, and the University of Massachusetts at Amherst, UC San Diego, and IIT Bombay. The important focus areas in the alliance include natural language processing, deep learning, computer vision, and others.

The centre for excellence is expected to come up on the campus in the next six months.

Experts Speak

Michael Karasick, Vice President, Global Labs at IBM Research says, “While working with AI systems, organizations require explicit reasoning and comprehension to reach a particular conclusion. We believe advancement in AI can tackle such problems”. He further adds, “We are excited to collaborate with IIT Delhi to focus on this area of research and empower organizations to make informed decisions by infusing key characteristics like reasoning, comprehension and transparency in their AI systems.”

Speaking on the important alliance, Prof. V. Ramgopal Rao, Director, IIT Delhi, says “India has immense talent to accelerate innovation in AI and related technologies. We are happy to collaborate with IBM Research scientists and provide opportunities to our students and faculty colleagues to work on some of the complex problems around AI and apply the solutions to real-world scenarios.”

AI initiatives at IITD

IITD currently offers undergraduate and postgraduate level courses in artificial intelligence. With this centre for excellence, the institute aims to bring researchers across departments, to find solutions for various problems and inculcate AI in their respective disciplines. The institute has around 40 faculty members at present who are working on AI with 10 people working on core artificial intelligence capabilities. With this centre, the institute wishes to create a single platform integrating all researchers to come together on a single platform. Besides this collaboration, IIT-D also plans to offer certificate courses in AI for professionals who may have graduated some years ago and need to reskill themselves to stay in the competition.

Embracing AI in India

AI has become a disruptive force to redefine technology and challenge the way we live. The Impact of AI has been felt in India, as per a Niti Ayog’s paper on National Strategy for Artificial Intelligence, the country has 386 AI and emerging technologies Ph.D. researchers of a total of 22,000 present worldwide, which ranks India on the 10th spot globally. These statistics make the IITD-IBM collaboration a great deal to cheer up for.

Read Source Article  Analytics insights

#AI #IBM #environment #IITDelhi

The AI-hype would have you believing that we'll soon be enslaved by super-intelligent beings or hunted by killer robots. Before building that Soviet-era bunker to survive the AIpocalypse, consider more immediate issues which are already affecting society today.

According to 23 AI experts Martin Ford interviewed for his new book, Architects Of Intelligence, the real imminent AI-threats relate to politics, security, privacy, and the weaponization of AI.

To understand how these problems affect society today, it's helpful to see them from the perspective of leaders which have helped shape the current AI revolution.

William Falcon: Why did you decide to write Architects Of Intelligence?

Martin Ford: When I started a software company in the 90s, I noticed the impact of technology on jobs. That's when I started thinking about the impact of AI and robotics on the job market. That led to two books, The Lights in the Tunnel and Rise of the Robots. 

 

The purpose of Architects Of Intelligence is to draw everyone - not just AI researchers - into the discussion of immediate impacts of AI which are already affecting our society today. The book aims to highlight what some of those issues are and to teach a bit more about the technology.

William Falcon: Who is the audience for the book?

Martin Ford: Anyone! Especially people with a strong interest in AI. The book is intended for a wider audience than just researchers and engineers working or interested in AI. I also included a section in the beginning for technical terms which might be implied in some of the discussions.

Everyone should be concerned with AI, how it has progressed and its impact on the economy and society. It's a bit like reading a book about relativity written by Einstein - some of these people have invented key AI concepts in use today.

William Falcon: What is the main takeaway for those readers not directly working on AI research?

Martin Ford: The biggest takeaway for them is that everyone agrees that AI is going to be disruptive.  They don't agree on details of what that looks like exactly, but this technology will have a massive impact on society.

William Falcon: After your conversations with these researchers, what are your views on AGI (artificial general intelligence)?

Martin Ford: The main takeaway is that everyone I interviewed has a different idea. At the end of the book, there's a survey asking what year AGI might arrive. The average is 80 years from now. But the main takeaway - on all the issues, not just AGI - is that there isn't a consensus.

Even on the question of a potential existential threat of super intelligence, is that something we should really worry about? Most of them were pretty dismissive of that and thought that it's not something we should be really concerned with right now. A few do take those concerns quite seriously, though and believe we should be working on a solution now, even if the advent of super-intelligent machines lies far in the future.

William Falcon: What are more immediate concerns we should be thinking about?

Martin Ford: Impact on privacy, our political system and security. We've already seen some of this impact on our political system from events like Cambridge Analytica. We also have to think about security as we rely more on AI-powered autonomous systems which can become more susceptible to hacking when humans are out of the loop. The big one everyone's really worried about is the weaponization of AI.

Recently, we've also started to see news about AI algorithms which have led to biased decisions based on gender and race in hiring and in other areas. These are all issues that are already happening today and will become much bigger in the coming years. Everyone should be concerned about this, not just AI researchers.

William Falcon: Now that we've identified some of these core issues, what are tangible next steps to starting to solve them?

Martin Ford: Some of this will have to enter the political sphere. We'll need to develop some forms of regulation in some areas. The people I spoke to do not agree that we need to regulate AI research, but instead suggest regulating applications.

Self-driving cars are one obvious example. Another is how facial recognition should be used. Even reading emotions can be used in all sorts of nefarious ways to manipulate shoppers or during negotiations.

Who are the researchers?

  1. *Yoshua Bengio (MILA lab, Université de Montréal).
  2. Stuart Russell (BAIR lab, UC Berkeley).
  3. *Geoffrey Hinton (Google Brain, University of Toronto).
  4. Nick Bostrom (Future of Humanity Institute, University of Oxford).
  5. *Yann Lecun (CILVR lab, Chief AI Scientist at Facebook AI, New York University).
  6. Fei-Fei Li (SAIL lab, Google, Stanford University).
  7. Demis Hassabis (Co-Founder, Google Deepmind).
  8. Andrew Ng (SAIL labAI Fund. Stanford University).
  9. Rana El Kaliouby (Co-founder, Affectiva).
  10. Ray Kurzweil (Google).
  11. Daniela Rus (CSAIL lab, MIT).
  12. James Manyika (McKinsey Global Institute).
  13. Gary Marcus (Founder, Geometric Intelligence. New York University).
  14. Barbara Grosz (Harvard University).
  15. Judea Pearl (UCLA).
  16. Jeffrey Dean (Head of Google Brain).
  17. Daphne Koller (Co-founder, Insitro. Stanford University).
  18. David Ferrucci (Founder, Elemental Cognition. Bridgewater Associates).
  19. Rodney Brooks (Chairman, Rethink Robotics).
  20. Cynthia Breazeal (Founder, Jibo. MIT Media lab).
  21. Oren Etzioni (CEO, The Allen Institute For Artificial Intelligence).
  22. Josh Tenenbaum (Department of brain and cognitive sciences, MIT).
  23. Bryan Johnson (CEO of Kernel).

* Often called the Godfathers of Deep Learning.

Read  Source Article  Forbes

#AI #article #AIexperts #Forbes #FutureofAI

Fintech is here to stay and rule it means using the technology to make finance much easier. New start-ups in this sector are making the lives of customers much easier by identifying and improving upon areas in the finance industry which were lagging behind in technology and proved to be a pains for the same. It is said that AI can and will continue to benefit the consumers including those in the FinTech space. Following are some of the concrete examples of how AI will serve you.

Chabot’s: A Chabot is a computer program which does conversations via textual and auditory methods. They are now implemented by a variety of financial institutions as self-servicing customer-facing tools.

Fraud prevention and detection: The Financial industry is dependent on a set of complicated rules. Humans have manually re-examined hoards of data. Human error in this process is unavoidable.

Process Analytics for Improving Customer quest: There are incompetences that customers face along their quest with a bank. Process analytics let banks to examine data for incompetence throughout the customer quest using social media, and the bank’s internal data.

Democratization of Banking Solutions: Banking services that were organically inexpensive to many consumers are now available. One certain service is wealth management. Wealth management advisors have been mainly aiming for people with plenty of assets.

Having Passion for travelling and having interest in AI sector is a mind-blowing combination. AI is set to be a game-changer for the travel industry it helps consumers and companies making travel much more easily. Let us see how it is done.

 

Enhanced Booking and Ticketing via Dynamic Pricing: Tracking price variations for travel and lodging can be tricky for travellers who are aiming for the finest time to book a hotel, flights or vacation packages. However, travel operators can assist heighten the customer feel by applying dynamic pricing tools that leverage predictive, or even viewpoint, analytics as the Hopper's travel tracking app is doing.

Improved Operations: Hotels and travel operators are also benefiting from AI's ability to heighten the efficiency of its activities with smart tools and approaches, such as the travel genome for consumer segmentation and dynamic consumer profiles via automatic, AI-powered dashboards.

Enhanced Customer Services: Chabot’s, or conversational AI, are helping to create the way of rising the customer experience. Hotel chains and other travel providers are using Chabot’s to raise the customer's experience by getting a new way to communicate with customers.

Some of the Start-ups Examples are mentioned below

AltexSoft:  AltexSoft assists travel industry companies, such as airlines and hotels, with improving the customer feel with Artificial intelligence technology to improve travel providers' offerings with tools such as fine fare forecasting and intelligent fleet, pricing tools, crew management decision-support systems, and conversational port for customer support.

 Hopper: Hopper is assisting travellers to get a great head start and fine forecast prices for different seasons with its active pricing-powered mobile app. The company apply forecasted analytics to assist consumers to know when to buy a travel promotion.

Mezi:  Mezi' (TaaS) platform is powered by Artificial intelligence to assist travel operators to enhance their workflow. It helps to improve and automate travel booking for corporate travel. It acts as a personal travel help using Chabot’s and travel dashboards to give an end to end booking service and data insight.

 

 

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