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For too long, human beings have focused on computational power and have been obsessed with the power of the mind, says Azhar Siddiqui. Here he explains, why we need to turn to our emotions, feelings and intuition to achieve a higher form of intelligence – and a human driven future.

Over the last 20 years we have witnessed almost all labour-intensive jobs move from human hands to robots or other complex machines. In the last five years, machines are being used to perform complex intelligence based tasks in areas of medicine, research, space exploration, quantum physics, climate change, infrastructure development and in almost all other areas outpacing human capacity to process information. Human progress today is almost completely dependent on machines. Without the internet which is the machine network, we will stop functioning as a modern society.  

Now here’s the interesting part: With this exponential growth of machine power, it is predicted that somewhere between 2030 and 2045, the neural networks in machines will be able to compute and process more data and at higher speeds than the neural networks in the human brain – an event known as technological singularity. Simply put, machines will outthink and outsmart human beings creating a more intelligent being per se. Artificial Intelligence will be more intelligent than human intelligence. 

What happens then is the subject of many debates with one side stating that machines will take over the world and another side who believe that machines will collaborate with human beings and accelerate human evolution further. So what is the future going to be like? Should we be scared and stop creating more intelligent machines that will eventually outsmart us and possibly make us their slaves? If we are to evaluate the scenario purely on the computation power or processing speed, then there is no doubt that at some point we will have to submit our dominant position to a more intelligent machine system – known as Artificial Intelligence. 

But, I am not threatened by the this predicament. For the name artificial itself means its not real. Human intelligence should not be evaluated only as computational intelligence based on the processing power of the brain. For humans can do so much more than just process information or compute. Humans can feel, humans can connect, humans can sense, humans can empathize. We have emotions and a unique sense called intuition. The problem is that we do not know how to tap into these emotions and the bigger problem is that we have programmed ourselves not to trust our intuition. We have been relying so heavily on our brain and focusing so much on the ability to algorithmically understand everything around us that we have forgotten how to feel and how to connect with the world around us.  

Human’s understood the mysteries of the universe long before the laws of gravity and physics were defined. The theories of the universe that we are revealing today are not a revelation, but rather a confirmation of what was already understood thousands of years ago by men and women who we call philosophers, oracles, saints or prophets. Where did their answers come from in an age where no computer or microchip existed? Clearly humans felt and connected not just through their minds but through other means. Maybe the answers came to them through thoughtful meditation and introspection. Maybe we simply listened more our feelings and were more in touch with our intuition. We knew how to balance the understanding of our universe between computational thinking, emotional thinking and intuitive thinking? 

Perhaps this is the greatest power of being human: To really understand and trust out gut as they say. Feelings that we cannot compute in 0s and 1s but feelings that still give us answers to so many questions that are mathematically impossible to equate. 

Today, we fear that we may no longer be the most intelligent life on earth because the machines we built will compute faster than us. But that’s just one part of who we are what we can do for the machines can’t feel or imagine.  In the future, machines will do exactly what they are built to do – process information. And hopefully, humans will learn to escalate to a higher form of intelligence.  We will better understand the universe and our place in it. After all this is what being human is all about. 

But this is not going to be an easy journey and there is a real danger that if do not consciously put a real effort into this evolution, we very well may end up living one of the Hollywood movies where we become slaves to our machines. We continue to place more and more emphasis on sciences, finance, production, data processing and in doing so we are becoming more machine and less human ourselves. We equate success with machine like productivity and evaluate progress through the equation of output of goods and services that have material or monetary value. We need to stop this obsession and learn how to balance it better with our humanness.   This is not going to come automatically for this requires us to learn the techniques and put in hard work and commitment required to understand our own humanness first. It will require the investment of our time, and our time right now is disproportionately skewed towards computing the whole universe in equations of IF and THEN. We need to change this obsession with the computational power and algorithmic logic and learn to trust the fact that there is another way for human evolution. 

We need a time-out. There is an urgent need to collectively as a human race have a greater understanding and appreciation for art, music, spirituality, humanity, and everything else that is not materialistic in value. We need to formulate more policies in our personal lives, in our businesses and in our governments not just for ourselves but for our entire planet. We need to accept that we are part of a macro ecosystem known as planet earth and we cannot simply use and abuse our planet in the ways we have been doing. We need to celebrate heroes who do good things versus only celebrate heroes who do things that make money. Our evaluation of life overall needs to be redefined from the never-ending chase of materialism to a higher cause of self-realization. Our current obsession is turning us into machines and if we try to compete with Artificial Intelligence by become machines, we will certainly fail. This is proven by the theory of technological singularity.  

But my hope lies in the fact that we are not machines, we are humans. We are not artificial, we are real. We can feel, we can sense and we can connect with each other and with the world around us in more than just one way. We are meant to have a higher purpose and perhaps it is the threat of something artificial that will push us to realize our true potential. 

So how do we counter the threat of artificial intelligence – just be more human!

Organisations have come to realise that, in an age where everything is available to everyone, customer centricity is key and experience has become the X factor. The focus is on technology, with artificially intelligent algorithms and new interfaces to meet the needs of the customer. But how can we ensure that we don’t “just digitise” and that people and their needs remain in the foreground? An analysis by customer centricity and artificial intelligence expert Nancy Rademaker.

In our current digital world, keeping the human at the centre of everything is a big challenge for most organisations. Living up to the ever-increasing expectations of the customer is not always easy to do and will require continuous investments and adaptations. Even though technology can act as a huge enabler to deliver the utmost convenience, transparency and personalisation, how can we make sure we don’t “just digitalise”, but keep the true human connection as a priority?

Emotional Data

AI Technology that can recognise our human emotions and tailor the response accordingly.

The Ambiguity of Human Connection

There are two sides to this problem and they are related to the ambiguity within the notion of ‘human connection’. One aspect that defines us is that we always long for a strong connection with our fellow humans. We literally want to get in touch with others. We want to have physical conversations. The pandemic has of course reinforced this in a dramatic way. I like to refer to this as the ‘connection of the FEW’, the dialogues we have (mostly between two people) in which empathy, emotions and non-verbal signals play a crucial role. Next to this, we also long for connection in a broader sense. As humans, we have an intrinsic need for a sense of belonging. In the past this used to be local – our family, friends and peers – but with technology playing a much bigger role, it has evolved to a more regional, national or even global setting. One in which we are constantly looking for communities we can connect to and where we can converse with like-minded people. The nature of this ‘connection of the MANY’ is much more remote and its dynamics are very different from the first meaning.

Technology Enabling Human Connection?

How to deal with these two faces of connection as a retailer? How can technology help – if it can help at all? If we look at the connections of the many, these have of course been massively enabled through the social media platforms that have been on the rise for the past decade. According to Hootsuite, internet users worldwide spend around 2.5 hours on these social media (by the way, the West is lagging behind here!), and this number is rising every single month. Technology has enabled us all to influence and be influenced 24/7. We share our adventures, our purchases and our personal emotions with whomever wants to read them. Our social ‘status’ is determined by the number of views, shares and likes. The big platforms got us ‘hooked’ on this sense of belonging and brands are using it to the max to create tribes of followers to increase their brand reputation.

But will we settle JUST for the connection of the many? Of course not. We want to interact with individuals, and we want to be treated as individuals as well. As customers, whether it be in B2C or B2B, we value highly personalised interactions. In fact, we EXPECT highly personalised interactions. We no longer settle for some generic recommendation; we want it to be tailored to our exact personal needs and preferences. For most companies, this turned out to be quite a challenge, and fortunately technology has come to the rescue. Once all the relevant data – the absurdly BIG data – are collected, smart algorithms powered by artificial intelligence can accurately predict what we as customers want (even if we may not consciously be aware of it ourselves!). Knowing what your customer’s favourite channel is truly matters. Delivering seamless experiences ACROSS channels will soon matter even more.

Now the question arises, is all this ENOUGH to deliver a great customer experience? Is it enough to make it easy for me to buy stuff or make reservations online? Is it enough if the recommendations consider all my personal data and behaviours? Isn’t the essence of our human ‘being’ that we are emotional beings? Could it be that technology can NOT personalise our experiences enough, because it is unable to take our current emotions into account as well?

The Next Frontier

This is where emotional AI comes in: AI technology that can recognise our human emotions and tailor the response accordingly. Leveraging our ‘emotional data’ will have increasing priority for many companies. Amazon, for instance, introduced the Halo, a new wearable device that constantly monitors your tone of voice to detect your emotional state. Amazon claims this is to track your health and wellness, but just imagine the wealth of data they acquire in this way.

But there are more elements than just our voice. Parallel Dots has developed technology to help detect sentiment or emotion in written text, which can be used to make written responses more accurate. Companies like Intraface and Affectiva can analyse facial expressions to detect people’s emotional reactions in real time, which can for instance help to determine how they react to specific scenes in movies or TV shows and where to put certain ads. The Affectiva technology is also being used in cars, with numerous applications to augment in-vehicle experiences. Just imagine the climate, scent, light or music in your car being adapted to your mood…

Many hurdles will have to be overcome for emotional data to be handled correctly. Not only are they more intangible and sensitive than our ‘regular’ personal data, but we will also need to consider cultural differences in expressing emotions, multiple reactions at once (e.g. with several passengers in a car), and external elements influencing people’s voices or face muscles. Until technology can solve the problem of human connection completely, especially in a one-on-one setting, we will remain in great need of human employees to take care of this. And to be truly honest, as a customer I am still very happy doing business with actual PEOPLE!

This artice first appeared in TWELVE, Serviceplan Group’s magazine for brands, media and communication. In the eighth issue, you will find further inspiring articles, essays and interviews by and with prominent guest authors and renowned experts centred around the magazine’s theme “A human-driven future: How humans are shaping the digital world of tomorrow”. The e-paper is available here.

Until the release of Amazon’s Echo, aka Alexa, the big players had paid little attention to voice technologies. In the meantime, there are numerous other variants, but which are the best known and which voice interface is the most suitable?

Today’s voice interfaces are a combination of two components, namely transcription and natural language processing (NLP). A spoken sentence is transcribed into text. This is analysed using artificial intelligence, based on which a reaction is generated and converted back to analogue speech via a speech synthesis (see also part 1).

Different classifications

Conversational interfaces are differentiated by whether they use so-called knowledge domains or not. Knowledge domains are digital structures that map knowledge around a given subject area.

1) Conversational interfaces with knowledge domains 

Conversational interfaces with knowledge domains are not just about parsing phrases, but about understanding the actual meaning behind a sentence. These types of interfaces are called smart assistants. Consider this sentence, which is simple for us humans: “Reserve two seats at a two-star restaurant in Hamburg!” – it is very easy for us to understand. We know that a restaurant can be given ‘stars’, that Hamburg is a city and that you can reserve seats in a restaurant. However, without this prior knowledge, it is difficult to make sense of the sentence. ‘Two Stars’ could just as well be the name of a specific restaurant. What two seats are and how to reserve them is then completely unclear. That a restaurant with certain characteristics in Hamburg is to be searched for, is also unclear. However, Smart Assistants should be able to precisely understand these concepts and therefore require special basic knowledge in respective domains such as gastronomy, events, weather and travel.

2) Conversational Interfaces without knowledge domains

Conversational interfaces without domain knowledge, such as Alexa, do not have this skill. Instead, they use a different approach. For a possible dialogue, sentence structures are specified during implementation in which variable parts, so-called slots, are defined. The spoken sentence is then analysed and assigned with a sentence structure. Subsequently, the component which generates the response to what has been said is informed of which sentence structure has been recognised by the given variable parts. The fact that this does not require any basic knowledge is clarified by the following sentence: ‘I would like to buy a red shirt’. At this point, the system does not need to know anything about clothes or colours because it just compares the phrase with given phrases related to buying a shirt. For this purpose, it is defined in the interface dialogue model that there is a sentence structure with an ID called, for example, ‘shirt purchase’. It is then subsequently determined that the sentence structure may have the following characteristics: “I want to buy a <colour> shirt”, “I want to buy a shirt in the colour <colour>” and “I want to buy a shirt in <colour>”. In this way, it also defines that there is a variable phrase (slot) named ‘colour’. The desired possibilities for this slot are indicated, e.g. ‘red’, ‘green’ and ‘yellow’. If the user utters the above sentence, the analysis shows that it has the ‘shirt purchase’ sentence structure with the value ‘red’ for the slot ‘colour’. In a correspondingly structured form, a back-end system can already begin to build something with this information.

The current key stakeholders

Until the release of Amazon’s Echo, aka Alexa, most IT companies had paid little attention to voice technologies. Although Siri was released with a bang, it was perceived more as a helpful tool rather than a whole new class of interfaces. However, the advantages of hands-free features for mobile devices were not to be dismissed and today each big player develops their own language solution. Here is a brief introduction to the current key stakeholders:

Amazon‘s Alexa

If you look at the Amazon product range, it is clear that Alexa is a logical development from already existing technologies. The Fire Tablets (launched 2013), Fire Phone (2014) and first Fire TVs (2014) were already equipped with voice control. However, Alexa’s ‘Voice Interface as a Service’ or ‘Alexa Voice Service’ technology is still not considered a Smart Assistant. Instead of analysing the meaning of sentences, they are simply compared in the background. When asked more complex questions, Alexa quickly bails out. The reason for this is that it only handles superficial knowledge domains that are not open to the developer. In addition, requests that can be expressed to an Echo must be very concise and not overly complex in their formulation. For example, films can be searched for using the name of an actor, or restaurants can be searched for by indicating the area. However, it does not get much more complex than this.

Google Assistant

Google Now was originally part of Google Search and was only searchable on the web. Later it was spun off to expand domain knowledge, making it more competitive with wizards like Apple’s Siri or Samsung’s S Voice. Last year, Google Now was replaced by Google Assistant. The extent to which the various knowledge domains in the Google Assistant are interlinked was impressively demonstrated at the Google Developer Conference with the ‘Google Duplex’ product. As a component of the assistant, Google Duplex can make phone calls to real people and make appointments for the hairdresser, for example, or even book a table. In doing so, the assistant not only accesses the appointment calendar, but must also have appropriate domain knowledge.

Apple‘s Siri

The story of Siri is a bit different. The Smart Assistant was developed by the Siri Inc. company and from the outset took the approach of analysing language by means of domain knowledge. Siri Inc. is a spin-off of the Stanford Research Institute (SRI). Fifteen years ago, SRI collaborated with these institutions on the CALO (Cognitive Assistant that Learns and Organizes) project, the experience of which influenced the development of Siri. Siri was released in the App Store in 2010 and Siri Inc. was promptly bought by Apple. A year later, Apple then officially announced that Siri is now an integral part of iOS. It has since been unrolled across all platforms. Most recently, the HomePod was released as a smart loudspeaker that reflects the current trend in voice interfaces and is comparable to Amazon’s competing product, Echo.

Microsoft’s Cortana

Microsoft’s Cortana was presented to the public for the first time in 2014 at a conference. Also designed as a Smart Assistant, Cortana features interesting reality-based adaptations. For example, a real assistant usually takes notes about their supervisor or client in order to get to know the person better and remember their habits. This is where Cortana uses a virtual notebook. For example, when being used for the first time, Cortana asks a few preferences in order to be able to provide personalised answers at an early stage. This functionality can also be prompted as needed. The key element of Cortana is Bing; Bing-based services allow you to make informal queries with the search engine.

Samsung’s Viv

Samsung has also been trying to establish intelligent software for their devices for quite some time, which naturally must also include a voice interface. In 2016 Samsung bought the company of Siri’s developers, Viv Labs. Viv Lab’s system fully relies on domain knowledge. Unlike its competitors, however, Viv is able to extend the knowledge base of external developers into new domains. As a result, the system should become more intelligent and be able to understand more and more. For example, imagine a whiskey distillery. With the help of experts, the Viv is provided with knowledge about the domain of whiskey and its products. In addition, a distillery shares all of its knowledge concerning wooden barrels and their production. The Viv domain knowledge now provides valuable expertise on which wooden barrels influence the taste of certain types of alcohol. For example, oak barrels provide whiskey with a vanilla flavour. If I now ask Viv what results in the vanilla note of a particular whiskey from said factory, Viv can answer that this taste is most likely due to oak barrel aging. Thus, Viv has merged both domains.

IBM’s Watson

To clear up any misunderstandings, IBM Watson should also be mentioned here. There is no ‘Artificial Intelligence Watson’ that understands everything and continuously accumulates knowledge. Instead, Watson is a collection of various artificial intelligence tools brought together under a common concept that can be used to realise a wide variety of projects. In addition, there are projects that serve to build up a large knowledge base. However, one should not labour under the illusion that each Watson project provides access to this knowledge. If you want to implement a project with Watson, you need to provide your own database – just as with any other machine learning toolkit. Among other features, Watson provides transcription (The IBM® Speech to Text Service) and text analysis (Natural Language Understanding Service) tools. If you want to implement a project together with Watson, you build on these two tools when implementing voice interfaces.

From analysing the problem to finding the right voice interface

Of course, there are many additional solutions, some of which are very specialised, but which also aim to break through the restrictions of the big players in order to offer more development opportunities. Now, the question naturally arises: But why all the different voice interfaces? As with many complex problems, there is no single universal solution. There is no ‘good’ or ‘bad’ interface. There are only ‘right’ or ‘wrong’ applications for the different technologies. Alexa is not good for complex sentence structures, but is great for fast conversions and is already widely used. On the other hand, while Viv has not been able to assert itself yet, it has the potential to understand random and complex sentences.

The selection of the right voice interface therefore involves choosing certain criteria, such as the application, focus, problem definition, needs of the target group and how open an interface is for integration into your own projects.

This is the second contribution of a four-part series on the subject of voice interfaces:

On the face of it, the SXSW is a pretty poor deal. You spend 12 hours on a plane and then rush around downtown Austin with 30,000 other lunatics for a week to listen to lectures and panels in air-conditioned 80s-style conference rooms. Doesn’t sound very inspiring. For me, the conference is nevertheless one of the absolute highlights of the year, because you’d be hard pressed to find a higher concentration of excellent speakers on current trends in the digital world. Read about the topics and lectures I am particularly looking forward to below.

Digitisation has arrived in society

In recent years it has become apparent that the times when you had guaranteed attention with the next hype platform or app in the market are over. The issues have no longer been revolving around digital services or the marketing behind them for a while now, because digitisation currently covers all areas of life. The impact of this process on society, working life, health and urban development will be the dominant themes of the conference, as they were in 2017. The same goes for the demand for specific solutions that include new technologies in product development and the creative process.

The perennial favourites: VR, AR & AI

Virtual reality continues to be a hot topic, especially in the creative industries. While the search for meaningful application scenarios outside the niche continues, augmented reality is preparing to make the breakthrough into a modern storytelling tool suitable for the mass market.

AI, on the other hand, is much more established: Data as the DNA of the modern world and ever better algorithms promise automation and increased efficiency in many areas. But how much of this will find its way into consumers’ everyday lives? Amazon Echo & Google Home are now in millions of homes, but currently lead a sorrowful existence as glorified light switches and Bluetooth speakers for Spotify. What do the truly smart assistants of the future look like in comparison? And how are various industry pioneers already using AI today for communication, data analysis or product development?

Blockchain self-awareness

This year’s theme for tech conferences is probably inevitable: the blockchain. The flagship project Bitcoin has evolved from a democratic, borderless payment system into an investment bubble for dauntless investors. But there is tremendous potential in the technology behind it. How will smart contracts and transaction-based systems change our economic life, business processes and, ultimately, marketing? Ethereum co-inventor Joseph Lubin has titled his lecture “Why Ethereum Is Going To Change The World” and the other actors in the blockchain business are not lacking in self-awareness. It will be interesting!

Gaming & eSports

Representatives of the gaming and eSports world are also confidently taking an increasingly prominent place at SXSW. Often ridiculed by outsiders, gaming has now become a dominant force in the entertainment industry. The professionalisation of the eSports scene reached new heights in 2017 with millions invested in tournaments and teams. So if you’re still around in the second week of the conference, you should drop in on the lectures of SXSW Gaming. It could be interesting to see what the industry’s ROI expectations look like and what opportunities there are in marketing.

Problem children start-ups & disrupting dystopia

In contrast, the start-up scene in Silicon Valley is experiencing a bit of a crisis. At last year’s elevator pitches, every second comment was “Nice idea, but what are you going to do in three months’ time when Zuckerberg copies you?” The stifling market position of the Big Four has noticeably cooled the willingness of investors to provide seed capital for new start-ups. How can start-ups continue to raise capital to make their ideas a reality and grow in a world dominated by Facebook, Google, Amazon and Apple?

A few months after the Trumpocalypse, the mood in 2017 was somewhat gloomy, a rather atypical level of self-reflection for the industry. In our enthusiasm for the digitisation of all areas of life, have we underestimated the risks of a fully networked and automated world? What will be left of the quiet self-doubt in 2018? The closing keynote from SciFi author & SXSW bedrock Bruce Sterling is likely to be an excellent barometer. An hour-long rant with subtle peaks against the self-loving tech and marketing scene will surely be a highlight once again. A fitting title for 2018: Disrupting Dystopia.

Away from the lectures

In addition to the lectures and panels at the conference, the event spaces of the numerous brands and companies will be another highlight. Exciting from a German point of view: the presence of Mercedes-Benz. The joint focus of the me Convention during the IAA had already indicated far-reaching cooperation with SXSW. Mercedes and Smart are now on the starting line in Austin as super sponsors and are hosting their own lectures and events on the topic of Future Mobility in Palm Park, right next to the Convention Centre.

In addition, visits to the brand locations of the Japanese electronics giants Sony and Panasonic are also likely to be worthwhile. In 2017, Panasonic exhibited numerous prototypes developed in cooperation with students on the subject of the Smart Home. Sony, on the other hand, devoted itself to VR.

The large number of lectures, panel discussions, pop-up locations and the numerous events off the official program make planning your SXSW visit a challenge. When you think back to your time in Austin on your flight home, you often realize that the most exciting lectures were those you caught by chance, that the best Brand Lounge was one where you just happened to be passing by and you only met the most interesting people because they were standing next to you in the endless queues. Resisting the temptation to plan everything in advance makes a visit to SXSW all the more interesting.

Auf dem Innovationstag von Serviceplan diskutierten der renommierte Münchner Philosoph und Kulturstaatsminister a. D. Julian Nida-Rümelin und Martina Koederitz, Vorsitzende der Geschäftsführung IBM Deutschland, gemeinsam mit Klaus Schwab, Geschäftsführer der Plan.Net Gruppe, über neue ethische Standards.