Skip to main content

Bots as a New Customer Interface and Operating System

 (Chat)Bots: Not a New Subject—What Is New?

Bot, find me the best price on that CD, get flowers for my mom, keep me

posted on the latest developments in Mozambique.

—Andrew Leonard (1996)

The topic of bots is new. Back in 1966, Joseph Weizenbaum developed with

ELIZA a computer program that demonstrated the possibilities of communication between a human and a computer via natural language. When

replying, the machine took on the role of a psychotherapist, worked on the

basis of a structured dictionary and looked for keywords in the entered text.

Even if this bot model as a psychotherapist only celebrated questionable success, such bots of the first generation with a firmly predefined direction of

dialogue and keyword controlled are still used in many places.

Especially in the past two years, bots have been experiencing a new quality and significance due to the fast developments of artificial intelligence,

platforms, communication devices and speech recognition so that the unfulfilled wish of Andrew Leonard in 1966 can finally become reality.

Communication and interaction are increasingly controlled and determined via algorithms. Bots and messaging systems are being hotly debated

and frequently have to serve as the mega trends of the years to come. The focus is primarily on communication interfaces that bring along efficiency

and convenience advantages as the next logical level of evolution. But it is

about way more than “Alex, order me a pizza please” or “Dear service bot,

how can I change my flight?”



The popularity of messaging and bot systems is increasing constantly.

Since 2015, more people have been using applications (apps) for communications than social networks. That is almost three billion people worldwide

every day. In Europa and in the USA, the platforms WhatsApp (approx.

one billion people) and Facebook Messenger (900 million) are mainly used,

whereby in Asia, WeChat (700 million) and Line (215 million) dominate.

Two of the most significant companies of today, Microsoft and Facebook,

announced in the spring of 2016 that will be focusing on bots in the

future. Microsoft, whose CEO Satya Nadella describes bots as “the next

big thing”, is said to be fully concentrated on the company-own personal

assistant Cortana in 2020 according to an analysis by the IT research institute Gartner. Instead of the current heavyweight Windows, robots and chat

platforms are to move into the focus of Microsoft’s strategy. All in all, the

Gartner Institute expects that in 2020, 40 percentage of all mobile interactions will be controlled by bots (Gartner 2015).

Comments

Popular posts from this blog

Possible Limitations of AI-Based Bots

 The examples above already show the present-day potential of AI-based bots. At present, these systems are still in an early stage and still have certain limitations and potentials for optimisation. Twitter Bot Tay by Microsoft Most bots at present are reactive service bots. Engagement bots that actively interact with the users as market and brand ambassadors go one step further. The most famous example here is the chatbot Tay by Microsoft. Microsoft removed Tay from the web apologetically within one day. The example shows that the uncontrolled training of bots by the community can lead to fatal consequences. AI systems still have to learn ethical standards. It thus becomes apparent that even bots require a kind of guideline. Like a journalist has to observe editorial guidelines, bots have to observe certain standards. The next generation of AI-based bots must control and create the possible room for communication. IBM Watson has been able to celebrate quite a few respectable resul...

What is Machine Learning

 The term machine learning (ML) as a part of artificial intelligence is ubiq- uitous nowadays. The term is used for a wide number of various appli- cations and methods that deal with the “generation of knowledge from experience”. The well-known US computer scientist Tom Mitchell defines machine learning as follows: A computer program is said to learn from experience E with respect to some class of tasks T and performance measure P, if its performance at tasks in T, as measured by P, improves with experience E (Mitchell 1997). An illustrative example of this would be a chess computer program that improves its performance (P) in playing chess (the task T) by experience (E), by playing as many games as possible (even against itself ) and analysing them (Mitchell 1997). Machine learning is not a fundamentally new approach for machines to generate “knowledge” from experience. Machine learning technology was used to filter out junk e-mails a long time ago. Whilst spam filters that tack- ...

What is Data Protection and Data Integrity

 As a matter of principle, when it comes to data protection, a differentiation must be made between personal data and data involving companies. As soon as inferences can be made to a specific individual and single data levels are being worked at, a moment has to be taken to consider: What is being processed? Is there already a business relationship? Which permissions or legal consent elements are at hand? Customer data may not be collected without permission and may also not be resold. Anybody who acts carelessly here can quickly render themselves liable to prosecution. In principle, the following applies however: Almost anything is possible with the customer’s consent. This is the reason why Facebook can act with the data to such an extent, because consent has been given, even if only few users have probably fully read and understood the Terms of Use. Likewise, a relatively far-reaching data processing in the scope of an ongoing customer relationship under the motto “for our own p...