AI Regulations

AI regulations – the need of the hour in an automated world?

In July 2017, an epic rebuke created waves on the internet, as two tech titans clashed. Yes, we are talking about the now infamous Elon Musk and Mark Zuckerberg cyber spat. The bone of contention was AI, and its impact on humanity in the future.

Musk has repeatedly sounded the alarm bells on AI and the havoc it could cause if not put on leash. He impressed upon these points in the National Governors Association Meet held at Providence, Rhode Island, earlier in July. Post this, Zuckerberg, in his Facebook Live chat, dismissed Musk’s claims and called him a naysayer. In fact, he called the Tesla Motors’ founder ‘irresponsible’ for such a negative outlook.

Not one to be left behind, Musk posted this response on Twitter:

While the spat will soon vanish from our memories, the spark remains ignited: are Musk’s claims well-founded? Do we need AI regulations?

First things first. What is AI?

To most of us, AI is a robot from the future that can do incredible things, including shape shifting. Thank you, Terminator, for that glamorous image of AI. But seriously, AI is not just a robot. Robots are containers for artificially-intelligent systems working in the background, making high-quality decisions.

According to AI researchers, there are three types of AI:

  • Artificial Narrow Intelligence (ANI)

These perform only specific tasks, like the Google AI that beat the world’s current champion in the ancient Chinese game, Go. It can do this and this task alone. Another example is the self-driven car that will hit the roads soon (and has already caused a death during trial phase).

Quite recently, the first loan that the BRICS Development Bank — a financial institution set up jointly by Brazil, Russia, India, China and South Africa — has approved for Russia is meant to fund a project that includes the use of AI in Russian courts to automate trial records using speech recognition.

  • Artificial General Intelligence (AGI)

Artificial General Intelligence thinks on par with humans. Imagine having a sane conversation with machines? Today’s chatbots might soon achieve that (with copious amounts of training, of course.) AGI is incredibly beneficial for us – building smarter homes, performing complex medical surgeries, eliminating loss of humans in wars, and much more.

  • Artificial Super Intelligence (ASI)

Creating something that’s much more intelligent than us? How will you control that one? Imagine having an army person who is incredibly strong that even tanks and missiles can’t harm, and is well-versed with all defence secrets. What happens when this commando goes rogue? Now imagine this in a real-world level.

Apocalyptic AI?

It’s not just Elon Musk that’s warning us about ‘summoning the demon’ with AI. Stephen Hawking and Bill Gates are telling us to be cautious too. We might empower computers to take high quality decisions that may be right from a machine perspective but incorrect from a human perspective.

Remember the Midas story? The greedy king asks for a boon by which all that he touches becomes gold. The wish is granted, not counting the human loss (Bacchus, the Roman God who grants the boon wants to teach Midas a lesson. When Midas accidently turns his daughter into gold, Bacchus reverses it).  Apply this situation in today’s world. A super-intelligent system, that doesn’t possess the emotions that we do, and can thwart all our schemes to defeat it, is in fact a demon! Think Skynet gone live.

It is possible that AI research may go out of hand and create self-evolving intelligent system that may prioritize its survival over humans. While a total human extermination may or may not happen, the encroachment of AI on predominantly human jobs is expected.

Already, the self-driven cars are taking centerstage, which will put cab drivers out of work.

Alibaba’s Jack Ma believes that excessive application of AI will lead to widespread chaos as unemployment will soar. He views a future of increasing divide among Haves and Have Nots, and geopolitical discord, as AI will cause power to be consolidated in the hands of a few. He goes on to say that the rise of AI will lead to a World War III. His reasoning is simple – “The first technology revolution caused World War I. The second technology revolution caused World War II. This (Artificial Intelligence) is the third technology revolution.”

Do any AI Regulations exist at the moment?

AI researchers are divided on the need for regulations. Some feel the regulations would prove to be detrimental to important technical advancements, as mentioned in this Stanford University report. They urge for tough transparency requirements and meaningful enforcement, as against narrow compliance that companies answer to in letter but not in spirit.  Some are working towards building base AI principles that would guide researchers towards building safe and beneficial AI, and are backed by the likes of Elon Musk, Stephen Hawking, Google, Amazon, Microsoft, to name a few.

Partnership on AI

The big names of Silicon Valley have come together to form the Partnership on AI that provides a platform for researchers, scientists, policymakers and public to share knowledge. The group has thematic pillars which root for safe and accountable AI.

Asilomar AI Principles

 

In Feb 2017, leading AI researchers convened at the 2017 Beneficial AI conference, Asilomar, California. The group discussed the advancement of human-friendly AI and suggested regulatory principles.

European Union and US Government say yes to AI regulation

The European Union, too, published a document in 2016, with the intention of putting AI regulations into place by 2018. Similarly, the US Government has also stressed on the need for AI regulations.

The essentiality of AI Regulatory bodies

With businesses around the world investing heavily in AI without heeding precautions or repercussions, AI regulations, are indeed the need of the hour.  But, excessive regulation that is misguided will only stifle innovation. Thus, it is essential for lawmakers and researchers to work hand-in-hand to form an AI regulatory body that would:

  • assess the goal of the AI project,
  • understand its benefits/disadvantages,
  • provide for any countereffects and ensure public safety

Having a law does not prevent cybercrimes, nor will it prevent antisocial elements from using AI for self-serving avarice.  Effective enforcement is crucial, and it is best if the regulatory body is formed as early as possible, because – Artificial Super Intelligence is coming, we just don’t know when.

defining new normals in CRM - 4 trends in spotlight

Defining the new normal in CRM – 4 trends in the spotlight

Do you remember the times we used to go to our neighborhood mom and pop stores for some quick errands? The shopkeeper recognized and greeted us, enquired about our family’s well-being, offered the product we regularly bought, and if the product was unavailable at that moment, offered to deliver it at our house at no additional cost.

And he did that for all his regular customers.

An excellent way to establish rapport and nourish a healthy relationship with customers, through personalization.

That’s exactly what CRM is about in 2017, only businesses do it these days with the help of computers and internet, for millions of such customers. Today, customers not only knock business’ brick-and-mortar doors, but also, online – via social media, apps, websites, and the latest addition to the CRM kitty, chatbots.

What drives CRM in 2017?

Rise of the bots

Chatbots are perhaps the next big thing after apps. Every brand now has one in place – whether on its website or on social media sites such as Facebook Messenger. These bots act as lead generators, capturing customer queries and providing them quick information.

Here’s the Adidas Women UK Chatbot that promotes fitness among women and helps them book fitness sessions.

CRM

We spoke more about bots in our previous blogs, ‘Chatbots – a botched play or a game changer?’, and ‘Batman or Superman – What should your business’ chatbot be?

Smarter Mobile CRM

Mobile CRM is no longer just providing data on salesperson’s smartphones, online and offline. Some of the new features in Mobile CRM apps are:

  • Geolocation – Enables salesperson to identify which customers are in their vicinity, allowing them to drop by for quick, meaningful visits. This leads to effective usage of the salespersons work hours.
  • AI – Smart assistants pull customer data from their social profiles to glean a deeper understanding of customers. This helps the salesperson stay informed on the customer and personalize the pitch better.

Data-driven Personalization

Personalization is more than a “Hi *|FNAME|* ” in your mass mailers these days. Brands are leveraging machine learning to analyze customer data and identify patterns in behaviour. This helps them recommend the right products at the right time to the right customer.

For example, brands can use geofences to identify customers in store vicinity, pull their data from the CRM to analyze past purchases and push customized offer messages to their smartphones.

Leveraging Crowdsourcing

Business are deepening engagement with customers via crowdsourcing. Customers, ranging from various demographic segments are pulled together for surveys, polls, discussions, and online forums to provide feedback on new products, services and more. This helps customers feel more invested in the process, while it enables businesses to directly engage with customers and gain insights for their product roadmap.

A company that put crowdsourcing to good use is perhaps Lego Ideas. It is a website that acts as a forum for Lego fans to come together and suggest new Lego set ideas and designs. Have a look at their portal!

Lego Ideas - crowdsourcing

CRM has undergone a sea change in the last few years, and with technological advancements in AI and machine learning, the transformation will occur at an exponential rate. Businesses, globally, are recognizing the benefits of leveraging these advanced CRM features to create exceptional customer experiences, and widen mindshare as well as wallet share.

 

Automated CRM, powered by machine learning that helps your salespeople do what they do best. Score more deals. Contact AgilizTech to learn more.

 

Batman or Superman – What should your business’ chatbot be?

The Batman vs Superman battle continues, but this time in the realm of chatbots.

The dark knight is admired by many as he is the superhero sans any superpowers. He can’t fly, he doesn’t have immeasurable strength. But what he does have – excellent deduction skills, martial arts prowess and of course, tons of money. And in today’s world, Batman can exist.

Superman, on the other hand, is an extra-terrestrial messiah, who has extraordinary strength and can fly around (no thanks to the cape).

And when we take this analogy to chatbots, Batman is our trusted Retrieval model chatbot, while Superman is the Generative model.

We spoke about chatbots in our previous post, Chatbots – a botched play or a game changer?, and in this post, we dive a bit deeper.

Now what are retrieval and generative models?

Retrieval Chatbots

Retrieval chatbots can be understood in the form of a database and queries. There are scripted answers to scripted or near scripted questions. Let’s take an example.

Josh – the book recommending bot

Josh is a virtual assistant bot that suggests books depending on the genre entered by the user. Ben wants to gift his 9-year old niece a book. Watch how Ben (the user) interacts with Josh.

Retrieval Chatbot example - Josh

Here, the chatbot is retrieving titles as per the genres listed in its database and suggesting books to the user. This is a matching mechanism at work. A query is fired and that fetches a response from the database. Easy, peasy.

But many bots are failing this spectacularly, by not being able to tackle out of syllabus questions. Or not being able to empathize, to understand sarcasm or the worst of all, irony.

Retrieval bots are slowly improving and with breakthroughs in NLP, we might just be able to make them work better.

Generative Chatbots are different in the sense that they don’t follow the script.  They communicate with human users and learn to think on their feet and offer new lines.

Alice is an excellent example of an artificial intelligence bot that can have a fairly reasonable conversation with humans. No wonder, Alice won the Loebner prize thrice! Apple’s Siri is another amazing goal-based dialog agent. But these agents follow given heuristic patterns. Generative chatbots are those that use probabilistic techniques on existing data and create new lines. Deep Neural Network is the breakthrough technology that is helping shape generative chatbots, such as the LnH.

A Twitterbot , the LnH: The Band can compose on-demand new music based on the genre entered by the user. It has created 700 such new songs!

 

Let’s now look at another example of generative chatbots – Microsoft Tay. Tay, for those who aren’t aware, was the conversational AI chatbot that interacted with Twitter users and learnt with each tweet. It generated new content on its own, depending on what was tweeted to it. It was going pretty well, until people started training it to post racist comments.

A timeline view of Tay going from angelic to NSFW:

It becomes especially difficult when the chatbot has an open domain setting, that is, in the absence of a very specific goal. The chatbot cannot be programmed for just a few keywords and must communicate intelligently with the human on a larger set of topics. It sounds impossible, but research on deep learning is still on to make generative models work. The who’s who of the tech world – Google, Facebook, IBM and Microsoft – is piling up billions of dollars to solve the question mystifying us all – intelligence.

What chatbot should my business adopt?

It may seem like a fire or frying pan situation as Generative Chatbots are unpredictable and Retrieval Chatbots don’t know to handle irregular situations. So, the best solution, that businesses ideally ought to follow are a combination of Retrieval and Generative chatbots. Superman and Batman combined?

Excellent deduction plus massive strength?

Since that may be awhile in the oven, businesses are now going the retrieval mode. We looked at some of the top businesses out there using retrieval chatbots:

  1. Burberry

A renowned name in luxury fashion, they spare no expense for their bot, the Burberry Messenger Bot, either. Users can enter product keywords and browse through new products.

The chatbot displays a teaser video and provides a key button to touch. This speaks volumes of how the brand is trying to increase the bot’s appeal and thereby enhance customer engagement.

2. Dominos

A bigshot in the fast-food industry, Dominos helps its customers order pizzas using its chatbot for door delivery and carryout. The customer can now order via the Messenger chatbot and just pick up the order from the outlet when it is ready. The bot also offers order tracking facilities so that you don’t need to keep calling the delivery guy a hundred times.

 

3. Ebay

Conversational Commerce anyone? Ebay is on Messenger now, and it offers personal shopping assistance in the form of ShopBot.

Batman, that is, retrieval chatbot seems to be a safe bet – it is trained to answer specific questions and achieve a specific goal. You can be assured of not finding any grammatical errors, but be ready to face some annoyed customers when they at times it prompts “I am unable to understand that.”, or something of that sort. Retrieval chatbots do not yet possess artificial intelligence and it may seem like ‘the person is there but the lights are dim’. But the most important point is that they can be trained better using NLP and Machine Learning. Generative Chatbots are still not there yet. The work is on, and we are on the brink of technological advancements that can make these chatbots come alive with intelligence of their own.

At AgilizTech, we believe that chatbots are going to be the medium of B2C and B2B conversation in the near future. We’re exploring this exciting new realm of possibilities and are gearing up to leverage AI and Machine Learning to build revolutionary chatbots.