Month: April 2021

Artificial intelligence technology has developed in leaps and bounds over recent years and private sector organizations are increasingly leveraging AI and machine learning for everything from customer service to data analysis. The successful implementation of AI has allowed for processes to be optimized whilst costs are cut, and lead to greater customer satisfaction at the same time. Whilst government and public sector services have been slower to recognize the value of AI, there are many applications for conversational AI in this sector. Let’s take a look at the role conversational AI can take in government and public sector services.

The State Of Public Sector Services

Public sector services are still waiting for the technological revolution. Whilst some services have gradually shifted online — and this process was forced to speed up in response to the global pandemic in 2020 — government services are still heavily reliant on physical interactions and documentation. For example, queuing at the DMV and wrestling with complex systems of forms are commonplace in interactions with public services. These costly processes, requiring heavy investment in personnel and infrastructure, could be streamlined through the use of AI, creating optimized systems that offer streamlined and economically efficient models for public services.

User Expectations

Whilst the gap between public and private sector technological uptake tends to be significant, users of services in these dual spheres have no such gap in their expectations. As AI is rolled out in customer service roles in the private sector, consumers enjoy faster response times and improved service. These expectations also scale from older to younger users — millennials and gen Z in particular are used to operating in virtual environments and expect digital solutions to a range of problems. “Failing to meet user expectations is problematic within any demographic,” says Charlene J. Davis, a writer at Assignment Help and OXEssays, “but amongst younger generations, a failure of government can have significant ramifications for faith in the public sector as well as enthusiasm for partaking in civil society.” Conversational AI will be vital as governments face up to the challenge of meeting user expectations.

Trending Bot Articles:

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

The Rise Of Chatbots

Perhaps the most recognizable instance of conversational AI in customer service roles is the chatbot. Chatbots have become almost ubiquitous, sprouting unprompted on a wide range of websites from online banking to clothes shopping. By being programmed to understand keywords, chatbots can assist customers with a range of issues. “At their most simplistic, a chatbot can simply act as a dynamic FAQ,” says Alejandro H. Brennan, a chatbot expert at Revieweal and Custom Writing Services. “In this form they can help users to navigate websites — many government services from welfare to pensions could easily implement chatbots to assist users through complex tasks.” Chatbots can also be valuable for dealing with customer complaints — when programmed with more sophisticated natural language AI chatbots can seamlessly replicate human assistants — without the wait times.

Already across America forward-thinking local government entities have implemented chatbot technology to great success. As a case study, the experience of Los Angeles has been informative: a chatbot built by the city has been fielding questions from local businesses throughout the pandemic.

New Tech: Voicebots

Because many public services still rely heavily on phone lines, chatbots have a limited scope in the public sector. In this sphere, voicebots can be implemented to cut user wait times on phinelines to zero. Voicebots are valuable because their intuitive interface is accessible to a broad range of citizens, and they can be deployed to handle a wide range of common queries. In Mississippi, for example, local governments have integrated information about filing taxes and vehicle registration with Amazon’s Alexa — meaning that citizens have a wealth of information at their beck and call.

Conclusion

Inertia within the public sector often creates a resistance to the adoption of technology. But private sector experience has now demonstrated beyond all doubt the efficacy of conversational AI in revolutionizing customer facing roles. Chatbots and voicebots can be easily integrated with existing services, and AI can be cost-effective and exceptionally efficient. Indeed, as conversational AI is rolled out by public services, we’ll see the vital role it has to play in empowering younger demographics to engage with social services and civic institutions. The technology has arrived.

Bio: Lauren Groff is a writer at Write My Paper and Big Assignments. Lauren writes about science, technology and AI developments, and is fascinated by the rapid pace of innovations and their implications for wider society. Also, she is a blogger at Assignment writing services.

Don’t forget to give us your 👏 !

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Revolutionary Technology: Why The Public Sector Needs Conversational AI was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

What We Learned at the European and African Summits in 2021

Edinburgh, Scotland is a hub of conversational AI – littered with startups, labs, established businesses, and University departments focused on the topic. As an industry-funded Conversational AI PhD Researcher, I was approached by Sydney to help organise the European Chatbot and Conversational AI Summit in Edinburgh.

Of course, the event was eventually hosted online due to COVID, but that just meant we could invite even more attendees to watch our fantastic lineup of speakers.

I also agreed to help organise the African event, the first of its kind! This event highlighted many wonderful applications of this technology in Africa, but also the great range of challenges we have yet to tackle. I unfortunately have to stand down as a co-organiser of these events (due to the time my research demands), but I am looking forward to attending the Ibero-American event in May. If you want to be involved with these events in any way, you can contact Sydney here.

Without further ado, let’s run through a few event stats and then highlight what we learned at these two events.

Stats

In February, at the European event, we hosted 1,200 attendees to hear from 46 speakers.

Dr Kulvinder Panesar said: “This is the best paid conference I have been to – especially in my niche area, conversational AI and NLP, which I have been part of for the last decade. The sessions, that I tapped into, were amazing and inspiring with great speakers and discussions. I now have some great names to connect to. Thank you very much.”

In March, at the African event, we hosted 1,000 attendees to hear from 44 speakers.

An attendee said: “I would like to say thank you for the conference. It was very interesting for me as a linguist, who stumbled across the field of conversational AI last year.”

Overview

In total, we had 67 sessions over the two events. I have therefore decided to share a 1–2 sentence message from each session. I have also linked the session’s recording on Youtube for on-demand viewing. This is essentially a catalogue for you to browse bit-by-bit at your own pace. I will run through them in the following order: keynotes, panels, speakers, workshops, and exhibition.

Keynotes

Title: Chatbots for Social Good – Addressing the Conflict Between User Requirements, Technical Constraints, and Ethical Considerations
By: Professor Michael McTear, Emeritus Professor at Ulster University

Message: Chatbots can benefit people when applied to mental health support, care for older adults, dealing with harassment, etc… but these dialogues don’t just require more complex interactions, they raise many ethical concerns.

Title: Beyond Bots: Bringing Natural Language to Chat & Scaling Self-Service Messaging Channels
By: Cliff Haas, VP of Messaging, Sales and Strategy at Inference Solutions

Message: Almost half of customers won’t do business with a company if they can’t provide online chat and messaging channels, so you must know how to deploy IVAs quickly, affordably and effectively.

Title: Conversational Journeys
By: Ries Deijkers, CEO and Founder of Chatbots.Expert

Message: Classic customer journeys are moving to conversational customer journeys, enabling a new kind of business process automation and optimisation.

Title: The Impact and ROI of AI/NLP Chatbots
By: Stewart Mackay, Team Lead at CM.com

Message: There are many huge benefits of rolling out conversational AI to both the consumer and organisation, but there are benefits to the contact centre agents too.

Title: What Does the Future of Conversational AI Innovation Look Like? Do I Have the Knowledge Needed to Keep Pace with Innovation?
By: Sasha Caskey, CTO and Co-Founder of Kasisto

Message: Understanding the future of conversational AI can help address uncertainties and empower your organisation to adopt AI into your customer experience and support models.

Title: Can Chatbots Serve Africa?
By: Frederick Apina, CEO of Belltro

Message: Africa has been seeing slower adoption of chatbots due to poorer understanding of how chatbots can add value to businesses, but that is now changing.

Panels

Title: Conversational AI for Good
Members:

• Alice Smith, CEO of SpeakUnique
• Angus Addlesee, PhD Researcher at Heriot-Watt University
• Christina Boididou, Data Scientist at the BBC
• Pooja Jain, CEO and Founder of CogniHealth
• Saturnino Luz, Reader at The University of Edinburgh

Message: The performance of voice technologies can improve our lives and these five people are doing exactly this. The panel discussed synthetic voices, digital companions, ethical considerations for the mass market, using speech to improve healthcare screening, and voice accessibility.

Trending Bot Articles:

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

Title: The State of Conversation Design and Future Trends
By:

• Brynn Chadwick, Lead Product Designer at NIB Health Funds
• Greg Bennett, Conversation Design Principal at Salesforce
• Hans van Dam, Co-Founder and Dean at the Conversation Design Institute
• Nikki Dunagan, Conversation Designer at Oracle
• Srini Janarthanam, Conversational AI Engineer at NatWest

Message: Companies developing Conversational AI experiences need to look beyond the technology to the implementation and design of dialogue to achieve success and sustainability. This panel discussed how their organisations (of various sizes and industries) approach this work, the tools they use, their team operations, and key insights they leverage in their design strategy.

Title: Conversational AI in the Service Industry
By:

• Kirill Elsukov, Head of Innovation Lab at PIB Cardif
• Marco Li Mandri, Principal Product Owner at ING
• Ruth Engemann, Conversational AI Designer at E.ON
• Shnay Chohan, Senior AI Product Manager at NatWest

Message: The current state of the art Virtual Assistants can be built at scale to create huge financial benefits. This panel discusses the best practices to do this, and how to prepare the road for the future.

Title: Voice Assistants and the Path to Ubiquitous Computing
By:

• Anshumali Baruah, UX Designer at Deutsch Telekom AG
• Christine Hart, Global Voice Coordinator at Nestle
• Hannes Ricklefs, Lead Architect at BBC
• Jeff Dalton, Assistant Professor at The University of Glasgow
• Mohamed Hassan, Senior Voice AI Experience Architect at VUI Agency

Message: This panel discussed how Voice and Virtual Assistants are stepping stones towards ubiquitous computing. They focused on the impact on users, brands, tools, technology, research, and what each of these areas are doing now to prepare for this future.

Title: AI and NLP at the Intersection Between Academia and Industry in Africa
By:

• Eunice Mutahi, Data Management Associate at Evidence Action
• Luke Okelo, Lecturer at The Technical University of Kenya
• Mutembei Kariuki, Co-Founder of Fastagger
• Tunde Oladimeji, Technical Program Manager at Facebook

Message: Conversational AI is starting to become a part of people’s everyday lives in the continent of Africa. This panel discussed the current challenges to focus on within African society, using this technology.

Title: African Digital Renaissance – How African Researchers are Creating Data and Models for NLP
By:

• Jade Abbott, Senior Machine Learning Engineer at Retro Rabbit
• Joyce Nakatumba-Nabende, Lecturer at Makerere University
• Paul Kennedy, Community and Communication Manager at Zindi Africa
• Thierno Ibrahima, Lead Data Scientist at Baamtu

Message: For NLP to progress further in Africa, the many African languages need to be digitised. This panel discusses the organisations driving this from speech recognition in Wolof, to machine translation into Luganda.

Title: Conversational AI in Africa – The Promises and Pitfalls
By:

• Antoine Paillusseau, CEO of FinChatBot
• Frederick Apina, CEO at Belltro
• Harmony Mothibe, Founder of BotsZA
• Johan Steyn, Senior Manager at IQbusiness
• Michal Stanislawek, CEO at HearMe.AI

Message: Conversational AI can open the door to better service delivery in Africa’s rural areas. This panel discusses how we can adapt this technology for markets in Africa, and what pitfalls to avoid in the process.

Speakers

Title: Social Conversational AI
By: Alexandros Papangelis, Senior Applied Scientist at Amazon Alexa AI

Message: In order to make conversational AI suitable for social interactions we need to work on knowledge-grounded conversations, new dialogue policies, and commonsense reasoning.

Title: Using Voice Games as a Marketing Tool
By: Karol Stryja, CCO of utter.one and Michal Stanislawek, CEO of HearMe.AI

Message: Voice games can be grown organically and used as marketing tools for brand awareness. There also needs to be more tools that support various European languages, like Polish.

Title: Utilising Avatars to Create Social Presence Online
By: Gregor Hofer, CEO of Speech Graphics

Message: Emerging technologies can generate vocal cues as well as gestures and expressions, to convey socially richer information, which ultimately creates the perception of social presence.

Title: Conversation-Driven Development
By: Alan Nichol, CTO and Co-Founder of Rasa

Message: It is impossible to anticipate all the things your user could say but conversation-driven development, a blueprint for applying conversational AI practices, can be used to develop AI assistants that continuously improve over time.

Title: Designing Voice Interfaces for Kids
By: Luke Janissen, Conversational Designer at Greenhouse BV

Message: Many adults find it ‘awkward’ talking to a voice assistant, but this is not the case for children. Child-focused voice apps need to can therefore be used to educate children, while remaining fun, if designed correctly.

Title: Safety for Conversational AI
By: Verena Rieser, Professor of Conversational AI at Heriot-Watt University

Message: Commercial conversational AI systems rely heavily on hand-written rules and templates, whereas research systems apply neural end-to-end methods for response generation. These neural response generation systems raise safety concerns due to the lack of control.

Title: Building Blocks for Bots: How to Design and Orchestrate Complex Bots
By: Sascha Wolter, Chief Advisor of Conversational AI at Deutsche Bahn

Message: There are several conversational patterns which help to tackle complex interactions beyond simple FAQs. These patterns are also reusable, creating a kit that includes process models, advanced conversational designs, and creative technical approaches.

Title: Use Cases and Challenges for Voice Interactions in the Auto Industry
By: Jesús Martin, Senior VUI Designer at Amazon Alexa Auto and Shyamala Prayaga, Digital Assistants Product Owner at Ford

Message: Voice assistants are extremely beneficial in the Automotive industry, allowing people to keep their hands on the wheel and eyes on the road. This environment poses a set of new challenges however.

Title: Conversational AI – Beyond the Magic
By: Maaike Groenewege, Conversation Designer at Convocat

Message: Deep learning will not instantly create perfect chatbots for you, it requires a lot of human effort in reality.

Title: Conversation Design Best Practices – Enterprise for Customer Support
By: Greg Bennett, Conversation Design Principal at Salesforce

Message: The Einstein Bot Builder can help make your chatbot design process quick and easy (in English).

Title: Five Things to Consider When Investing in Chatbots
By: Anand Tamboli, Author and Speaker at Anand Tamboli & Co

Message: Conversational AI is a substantial investment but they are not simply technology projects, they have larger impacts on other parts of your business, so it is vital to ask the right questions and invest in the right solution for you.

Title: Investing in Bots – Product Development Circle
By: Casper Guldager, Manager and Head of Sales at KPMG NewTech

Message: Successful investments into chatbots can enable organisations to deliver on the future needs of customers and result in an operation with close to zero cost of scale.

Title: Getting a Job in Conversational AI
By: Allys Parsons, Conversational AI Recruiter and Co-Founder of Techire AI

Message: Conversational AI can be a bit of a minefield when it comes to figuring out the right roles to search for, the skills to highlight, and the salary to expect.

Title: Expanding the Chatbot Capabilities to the Telephone Channel
By: Livio Pugliese, CEO North America at Interactive Media

Message: Digital channels now carry the majority of customer service interactions, but the traditional phone channel is still busy. Integrating chatbots with the telephone is worthwhile but not trivial, with several obstacles in terms of technology and conversational experience.

Title: Chatbots for Customer Service – Saving Money and Time
By: Sahar Gebreil, Chatbot Specialist at the Federal Tax Authority in Dubai

Message: Chatbots allow companies to regain time which they can use to grow their business.

Title: Voice Assistants as a Brand’s Digital Front Door – 5 Key Learnings
By: Christoph Esslinger, Managing Director at VUI.Agency

Message: In the coming decade, we will see voice assistants becoming the main entry point into a brand’s universe. The ability to just speak out your wish or question to a trusted virtual representative will become the starting point of a user’s journey.

Title: The Omnichannel Solution – Chatbots and Voice
By: Gary Williams, Director of Sales and Consultancy for UK and Ireland at SPITCH and Liam Ryan, Sales Director at Creative Virtual

Message: Seamless omnichannel support (advancing beyond a multichannel approach) allows users to type, tap, and talk across channels – never having to start over as they begin interactions in one channel and continue it in another.

Title: Voice Interaction in Mixed Reality
By: Matthias Wölfel, Professor at Karlsruhe University of Applied Sciences

Message: Speech is considered the most natural way to communicate, but experiments show that there isn’t always a benefit to the user in virtual reality. In mixed reality however, voice interaction can be incredibly helpful.

Title: The Proven Conversation Design Workflow
By: Hans van Dam, Co-Founder & Dean of the Conversation Design Institute

Message: By following a good conversational design workflow, your various teams can unify the best of technology, psychology, and language to unlock the potentials of conversational AI.

Title: The Path to True Transformation with CAI
By: Kane Simms, CEO of VUX World

Message: Conversational AI is often stuck within the development phase, as organisations struggle to scale it into business as usual. Scaling while maintaining a conversational AIs quality is possible though.

Title: Let’s Free Humans from Boring Tasks
By: Andres Pulgarin, CEO of BotsLovers

Message: Many people spend their days answering the same customer questions on the phone, through chat systems, through social networks, email, etc… We can use conversational AI to take these tedious questions, leaving humans with more time to work on the interesting tasks.

Title: Conversational AI – Unlocking the Future of Africa
By: Johan Steyn, Senior Manager at IQbusiness

Message: The African tech industry has seen a remarkable surge over the past few years and conversational AI will play a crucial role in the development of commerce, education, wellness, and healthcare in Africa.

Title: Impact of Deep Learning Based Chatbots in Reducing Attrition
By: Raul Villamarin Rodriguez, Dean of the School of Business at Woxsen University

Message: Employee engagement and retention can be very challenging, especially if their work involves repeated tedious tasks. By incorporating chatbots into your workflow, you can reduce the burden from your staff and reduce attrition.

Title: Conversational Interfaces in an Insurance Company
By: Kirill Elsukov, Head of the Innovation Lab at PIB Cardif

Message: Innovation in big companies is known to be very challenging but Cardif Russia integrated a chatbot into its websites and developed a conversational agent that serves 40% of their call centre’s incoming calls.

Title: Contextual Voice Experiences
By: Mohamed Hassan, Senior Voice AI Experience Architect at VUI Agency

Message: Users now constantly expect voice assistants to have better speech recognition and understand them better, but contextual design can really enhance future voice experiences.

Title: Operating a Chatbot on Your Own – From an Idea to a Data Machine
By: Henry Ginsburg, Conversation Designer at the University of the People

Message: If you are developing a chatbot on your own, then you need to: (1) plan and find the resources you need, (2) map and plan out the conversations, (3) launch and be ready to fix unexpected issues, and (4) continuously monitor and update for long term maintenance.

Title: Inclusive Conversation Design
By: Shyamala Prayaga, Digital Assistants Product Owner at Ford

Message: The voice assistant industry has boomed in recent years, and is expected to continue to grow significantly. There is a lot of focus on tools and resources to improve these systems for the majority of users, but we should also consider making them inclusive for all.

Title: Using Chatbots to Fight the COVID-19 Infodemic
By: Andrew Bredenkamp, Chairman at Translators without Borders and Rodrigue Bashizi, Community Engagement Officer at Translators without Borders

Message: There is a huge amount of information surrounding COVID-19 and it is difficult to keep up. In order to fight this “infodemic” with a chatbot, it must be able to have an engaging two-way conversation in several languages.

Title: Introducing Women in Voice, a community for women and diverse people working in or pivoting to the voice technology space.
By: Romina Pankoke, Director of Chapters at Women in Voice

Message: Women in Voice has been expanding vibrantly since it was founded in 2018. It now has a strong global community with 20 chapters in 15 countries on 5 continents.

Title: Chatbot Ecosystems Overview and Investing in Bots
By: Resham Sivnarain, Digital Technologist at Nedbank

Message: Chatbot ecosystems have become more and more interconnected and complex. These ecosystems are driven by a blend of customer needs and innovation, they need to be aligned with business needs for overall success.

Title: Develop a Google Action with Action Builder – Example for Kruger National Park
By: Menno Zevenbergen, Head of Conversational AI at Greenhouse BV

Message: Google released “Action Builder” in 2020 which can be used to build voice apps on Google Assistant with the latest technology.

Title: Making Technology Personal
By: Rishal Hurbans, Author and Co-Founder of Viszen.tech

Message: Technology has become an extension of us all, and we are teaching machines with almost every interaction we have. This data can be used to develop more personalised services.

Title: Conversation Driven Development
By: Eden Constantino, Machine Learning Engineer at the Disruption Lab

Message: It is important to have a user-centric development approach to ensure digital solutions in Africa are not just imported from other continents. The people in the UK and the people in Namibia are likely to use different phrases for example, so an imported solution will not perform as well.

Title: Representation and Inclusivity in Chatbot Solutions
By: Tumelo Setlaba, Co-Founder and Head of Operations of Enlabeler and Esther Hoogstad, Co-Founder and CEO of Enlabeler

Message: Local language datasets are rare so need to be prioritised through collaboration and community in order to ensure future voice assistants are more inclusive.

Workshops

Title: Rasa Workshop – Conversations from the Command Line
By: Vincent Warmerdam, Research Advocate at Rasa

Message: Starting from scratch, you will build a voice assistant that you can talk to from the command line. Vincent also explains how the setup can be extended to handle Non-English as well as custom responses. The workshop is intended for a technical audience but you’re not expected to have in-depth knowledge of python. If you’ve got a modern laptop with python installed, you should be good to go for this workshop.

Title: Inference Solutions Workshop – Building Call Deflection to Chatbot
By: Cliff Haas, VP of Messaging, Sales and Strategy at Inference Solutions

Message: In this workshop Cliff builds an intelligent virtual agent that resides in an inbound call centre and acts to shift the caller to a chat session that automates fulfilling their needs.

Title: Chatbots.Expert Workshop – Mapping a Conversational Customer Journey
By: Ries Deijkers, CEO and Founder of Chatbots.Expert

Message: Ries hosted a workshop on mapping a conversational customer journey.

Title: Successfully Deploying and Accelerating Adoption of Conversational AI Technology in Africa
By:

• Justin Arnoldi, Head of Digital Transformation at Blue Turtle
• Ravi Govender, Digital Executive at Nedbank
• Sasha Caskey, Co-Founder and CTO of Kasisto
• Stephen Epstein, CMO of Kasisto

Message: Current digital trends are accelerating the adoption of virtual assistants within the banking industry. This requires new strategies to meet the ever-changing needs of banking customers on the African continent.

Title: Building your Next Chatbot Solution
By: Waziri Shebogholo, CEO of Belltro and Nyamos Waigama, Operations Lead at Belltro

Message: This workshop covered whether you need a chatbot, the chatbot building journey, and where to get started.

Exhibition

Finally, we had a virtual exhibition area for our sponsors. In alphabetical order for both events, go and check out:

• Belltro
• Blue Turtle Technologies / Kasisto
• Chatbots.Expert
• CM.com
• Conversation Design Institute
• The Data Lab
• Fluido AI
• Inference Solutions, a Five9 Company
• Interactive Media
• Rasa
• Spitch / Creative Virtual
• Techire AI
• VUI.Agency

Don’t forget to give us your 👏 !

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The Current State of Chatbots and Conversational AI across Europe and Africa – A Catalogue was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

For your company’s chatbot to know how to answer your customers’ questions, you need to have a good AI knowledge base.

In this article, you will learn what a knowledge base is, how important it is for a chatbot to operate, and how you can improve it to always get the best results!

What is an AI Chatbot?

A chatbot is an intelligent virtual agent used to optimize communication processes between companies and their customers. However, companies can also use chatbots as internal support for employees.

To learn more about internal chatbots, see the article What Can Internal Chatbots Do for Your Company?

Nonetheless, to be considered intelligent, these agents must possess certain characteristics. In other words, they need certain necessary technologies to have some form of intelligence.

AI for Intelligent Machines

When talking about machines, the term “intelligence” is much debated. We have always been taught that humans are intelligent because of their ability to develop reasoning.

But, nowadays, it’s already possible to program machines to mimic the thinking process of humans.

First, since we are talking about conversational agents, they need to understand and process human language. To this end, they need NLP or Natural Language Processing technology.

For a system to learn the human language, it is fundamental to have linguistic knowledge.

Learn here how important linguistics is in your chatbot.

Second, for the machine to imitate the learning process, it needs Machine Learning technology which, as the name implies, is the one that allows a system to learn by itself.

Find out all the details about Machine Learning here, what its algorithms are and how each type changes the behavior of your chatbot.

What is an AI Knowledge Base?

Well, we can divide knowledge bases into two poles. The first concerns the human knowledge base, and the second the “mechanical” knowledge base, let’s call it.

Generally speaking, a knowledge base is all the information acquired and needed to perform a certain task.

The Human Knowledge Base

The human knowledge base is typically known as “knowledge” only. It’s all the information that a person acquires from birth. All the experiences, the learning that is recorded in the brain.

One kind of knowledge is acquired through transmission, like when our parents tell us “don’t touch the oven or you’ll burn yourself” or when they teach us how to speak.

Another kind of knowledge is intrinsic to us, like learning to walk. Just by the experience of seeing other people walking, the baby, on its own, finds a way to start moving more effectively until, eventually, it starts walking.

Trending Bot Articles:

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

The Mechanical Knowledge Base

This type of knowledge is similar to the previous one in the aspect of transmission. That is, if the machine is not fed with data, it will never have any intelligence.

Even if we give it the ability to learn by itself, it will never “join the dots” without information.

So, long before a system or, in this case, chatbot starts to learn, it has to have data it can use — a knowledge base.

Put it like this: in chatbots, a knowledge base is a library that gathers structured and unstructured information.

From the structured information, the bot can categorize the unstructured.

Why Do You Need to Create a Good Knowledge Base?

As we have already talked about, the chatbot needs structured information to interpret and categorize the unstructured data subsequently.

But what differs a good database from a mediocre one?

A good database has all the information that is indispensable for the system to do its job well.

Just as we need to know a lot about baking to make a great cake, the same is true for chatbots.

If we want them to have a conversation as similar to humans as possible, then we need to give them all the information they need to make that happen.

Of course, your chatbot won’t need to have the same knowledge as a human being (yet). But it should be an expert on the topic. In this case, the product or service your company is offering.

The Easiest Way to Improve Your Chatbot’s Knowledge Base

“Okay. I already have a chatbot implemented in my company’s digital contact channels. The bot responds well to the questions asked, but it could still be better.” — you think.

Well! You don’t have to wait any longer because the answer is Visor.ai’s platform.

The Visor.ai platform is designed and regularly updated to be as intuitive to use as possible and to users make the changes they want independently.

During the setup period, Visor.ai provides templates that help the implementation be faster because they already include the basic information for each sector.

But beyond that, the Visor.ai platform offers several tools where you can edit and improve your chatbot or email bot’s knowledge base.

To learn more about automating the handling of incoming email, click here.

5 Features to Enhance your Knowledge Base

1) FAQs

The FAQs tool is where you can build up, so to speak, the overall interactions of your chatbots.

That is, this is where you include the most frequently asked questions by your customers regarding your products or services.

2) FAQ Conflicts

In the FAQ Conflicts, you can see the conflicts that the chatbot is having between different FAQs.

These conflicts come from phrases often having similar information and the chatbot not knowing which one is the most correct when answering the user.

3) Small Talk

Natural conversation between two humans is not only about scientific and interesting topics. Often it is the so-called “small talk,” conversation without much content, but which is also necessary to maintain a certain climate.

The same has to happen with your chatbot if you want to offer an alternative that is as similar as possible to human dialogue.

It is in the Small Talk of the Visor.ai platform that you define these dialogs. From “Good morning! How are you?” to “Who is your creator?” or “What time is it?”.

All these small talk options have to be present in your chatbot’s knowledge base.

4) Text Analysis

In addition to defining interactions, it’s important to give more detailed knowledge, namely words that have the same meaning or words that, appearing together (compound words), have a certain meaning.

This is where the Synonyms and Compound Words sections come in.

In the first, as the name indicates, you can add synonymous words.

For example, if you are part of an insurance company, you can say that “disaster” is the same as “accident,” “incident,” etc.

In Compound Words, you can teach the bot that it can take expressions like “citizen card” as one entity when analyzing user requests. As opposed to parsing word by word.

5) AI Trainer

Finally, in AI Trainer, you can check your chatbot interactions with your customers.

In this tool, you see all the new user sayings that are not yet in the knowledge base and how the chatbot answered them.

Again, the chatbot can answer questions that are not exactly the ones in your database because it has Artificial Intelligence.

In addition to verification, you can correct the interactions that the chatbot had doubts about and teach it the most appropriate answer. Additionally, you can directly add new FAQs.

This process allows you to increase the intelligence of your bot and make it more efficient.

To learn more details about how to train a successful chatbot, click here!

Conclusions

The Visor.ai team developed the NLP and ML technologies in-house to get the best results and meet our customers’ requirements and needs.

That means that all the knowledge about the human language, its rules, and so on are covered when implementing Visor.ai solutions.

The templates we told you about earlier also cover information related to a certain sector, such as Insurance, Banking, or Marketing.

However, there’s no one better than you to talk about your company or product.

You must include this information in your chatbot’s knowledge base yourself.

If you need help or more information, don’t hesitate to contact the Visor.ai team! We’re always available to hear from you!

Don’t forget to give us your 👏 !

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5 Tips to Create an Effective AI Knowledge Base was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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Artificial intelligence algorithms are widely used in e-commerce. For example, when creating chatbots. Technologies provide automated, prompt, and high-quality solutions to customer problems. Accordingly, they help to increase sales.

However, this is only relevant if chatbots are used correctly. Some mistakes completely negate the possibilities of technology. Today we will tell you about them. Find out 10 common mistakes companies make and how to fix them.

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10 wrong ways to use conversational AI for chatbots

Inappropriate conversations

An improperly programmed chatbot is capable of maintaining a conversation that is best terminated. For example, of an offensive nature. This happens when a chatbot is programmed to give standard “yes/no” answers without understanding the question. The implications of setting up to blindly repeat the user’s request are similar. Avoid this.

Internet trolls often entertain themselves by asking inappropriate, incorrect, or stupid questions. The chatbot must be able to identify this. And in such a way that the conversation ends. Programming to repeat the question, or send yes / no answers if the request is not understood, does not improve the quality of service. It damages the brand.

Misunderstanding the basics

Chatbots require prior programming by learning the appropriate words and expressions. With insufficient knowledge of the latter, a misunderstanding of the issues is possible. For example, Messenger had a Poncho chatbot that tells users the weather based on their location. He did the task well. However, the word “weekend” confused the program.

Chatbots answer user questions based on specific previously learned prompts. These are the given statements and words. Also, semantics can be used by spoken artificial intelligence agents. It allows you to understand the context without learning a specific formulation.

To eliminate misunderstanding, teach the chatbot the maximum number of words, situations, and expressions. Use crowdsources to collect additional data. Track engagement and continue regular training for the program.

Nonadaptation to the channel

Long messages containing more than 10 sentences are relevant exclusively on the site. The long answer is good. However, there is a high probability that the user will turn over the key information contained somewhere among the lines.

It’s easier for people to process small messages. Therefore, instead of several large paragraphs of text, limit the chatbot’s responses to a couple of sentences, or even one.

Lack of context awareness

Human communication involves many influencing variables. The meaning of a particular word changes depending on the situation, context, and subject of communication. This also needs to be taught to the chatbot. Otherwise, the program can forget everything previously written by the client and lose the thread of dialogue.

You can fix this by mapping out detailed conversation trees. Just take the time to do this. Managing expectations can also improve the quality of customer service by informing users about the limitations of chatbots.

Trending Bot Articles:

1. Chatbot Trends Report 2021

2. 4 DO’s and 3 DON’Ts for Training a Chatbot NLP Model

3. Concierge Bot: Handle Multiple Chatbots from One Chat Screen

4. An expert system: Conversational AI Vs Chatbots

Lack of investment in a supporting ecosystem

Artificial intelligence is at the heart of any communication platform. However, this does not exclude the importance of the ecosystem. For artificial intelligence, the quality of the data used in training/adaptation is critical. The infrastructure used to build is also important.

Therefore, machine learning programs must be dealt with. It is part of the supporting ecosystem. By investing in them, the company is accelerating the training of artificial intelligence.

Lack of effort to improve chatbots’ ability to communicate

The secret of the intelligence of chatbots is the use of artificial intelligence and machine learning technologies. However, the foundation is laid by man. Chatbots should be taught basic things, expressions, and words. Only then do the programs gain the ability to recognize and understand users’ questions in the process of communication.

The difficulty is that people express thoughts in different ways. It is necessary to systematically train chatbots using the conversation history. The more examples the program learns, the faster and more accurately it will be able to determine the client’s intent.

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No effort to improve the chatbot’s conversation skill

Simulating human conversation is not an easy task. However, it is possible to help artificial intelligence do it. To do this, you need to provide basic knowledge.

Provide the chatbot with answers to all possible customer questions. For example, after analyzing the previously set. Try to expand the list of possible answers by providing examples. Remember that a chatbot must communicate not only efficiently, but also competently.

Grammar errors in messages can spoil the support experience. To prevent this from happening, use services like Ivory Research. This guarantees literacy, readability, and consistency of answers.

Also, introduce the AI ​​to customer intent. This will help the program understand exactly where it needs help. Consequently, the chatbot will be able to determine how this can be done.

Inappropriate use of conversational artificial intelligence

Technology opens up many possibilities. However, there are situations where the use of artificial intelligence is impractical. For example, if the client has a clear understanding of what he needs. Then the technology only complicates the execution of the action.

Conversational AI is great for situations where the task is time-consuming. And so much so that the use of a tone menu or graphical interface will make it unnecessarily cumbersome.

Remember one rule: if a task cannot be completed using a fixed set of inputs, then conversational AI is needed. Most often these are nonlinear processes.

Making chatbots more complicated

Remember that chatbots do not replace people. They are designed to be supportive. Chatbots work great when you need to reduce the time and labor costs of performing repetitive tasks.

However, too many functions confuse them. Optimally, there should be 3–4 of them. Highlight the key tasks of chatbots and then they will perfectly cope with their duties.

Focusing chatbots solely on data collection

It’s a bad idea to build chatbots to collect data from users. They are tailored for other tasks. Chatbots are capable of providing automated, instant, and professional user support. Therefore, the key task is to improve the quality of communication.

The connecting function of chatbots in business communication with customers is the ability to understand questions and provide accurate answers. This creates sustainable values. Only after getting a positive impression of the company can the data from users be used to achieve better results.

Conclusion

For a client, interaction with a chatbot differs little from communication with a manager. It can also create a great user experience or ruin the experience of a company. Therefore, it is important to improve the work of chatbots. Avoid the above mistakes, help AI train, and provide excellent customer service.

Don’t forget to give us your 👏 !

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10 wrong ways to use conversational AI for chatbots was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

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