Do you remember what the Internet looked like twenty years ago? Web development has come a long way in the past few decades, from implementing newer web design standards to developing new technologies that can support customers beyond simple web forms and email. One could argue that the Internet is all the better for it – with communication made faster, simpler, and more efficient with the advent of tools such as chatbots.
In recent years, the explosion in AI development has helped to provide opportunities to expand the role of chatbots on the web – transforming it from a static response system to a tool that is much more dynamic, reacting to a customer’s needs on the go. For many of us, chatting to this new generation of chatbots can feel like talking to a real person.
A new type of chatbot requires new kinds of data—in the case of modern chatbots, that may mean that prompts, queries, and questions may be stored for future analysis and implementation within the system. In a world where cybersecurity threats are growing and evolving, let’s explore how those who choose to study a Masters in Cyber Security can be empowered with the tools necessary to assess and address threats.
The Challenges of Online Support
Getting online support can be challenging, even for the most organised customer. The web, by design, is available all the time – so for many consumers, there’s an expectation that they’ll be able to receive support no matter what time they’re online.
However, businesses’ ability to provide online support is often limited. While it would be desirable for customers to have help available 24/7, it’s not financially feasible, no matter whether you’re a small business like a bookshop or a large company like a technology retailer.
Traditional chatbots have also faced challenges in responding to customers’ needs. Earlier iterations of chatbots relied on text-based inputs that weren’t always retained for further analysis. This traditional method of running chatbots often has limitations, mainly as analysts cannot analyse customer chats to identify any issues they may have had and provide recommendations on improving such platforms.
Harnessing the Potential of Chatbots
As technology has evolved, artificial intelligence and machine learning developments have presented various opportunities for chatbots to enhance their capabilities. Take, for example, concepts such as natural language processing (NLP). By having the tools available to interpret human language, modern chatbots can interpret and understand sophisticated queries, connecting customers to the things they need when they need them.
Other innovations, such as personalisation, empower chatbots to discuss a customer’s needs directly. Harnessing a customer’s account information, a chatbot can readily support many customer concerns – and even, in some cases, effect change without needing real-world support staff.
Woolworths’ conversational AI platform, Olive, is one example of a chatbot that harnesses personalisation and NLP to get the most out of customer interactions. Using AI models and being hooked into Woolworths’ systems, Olive can provide information on the tens of thousands of products sold in supermarkets and even offer refunds for order mistakes and issues – an issue common in the rapidly growing online delivery sector.
Imagine placing an order online and only interacting with someone when the delivery is dropped at your door. This is an example of how chatbots can help make the customer experience more seamless for businesses and consumers.
Risks Around Contemporary Chatbots
Changes are often required to enable modern AI capability in chatbots. It’s not about patching in a new system and hoping it works – building a new chatbot from the ground up is often about creating a platform that works with data fundamentally differently than traditional chatbot systems.
That change of focus on data creates a new set of challenges. How is chat data managed – how is it stored, who has access to it after a chat session has concluded? On the data that’s entered, more questions arise – if a chatbot is designed to take payments, how does one structure a chatbot to ensure that it doesn’t reproduce sensitive data, such as credit card details?
There are many industry examples of chatbots being used and misused – from corporate data leaks, to software engineers generating software keys from defunct software platforms. While these may seem relatively benign, they highlight the risks that exist with modern chatbots and the data sources that they store and interact with.
As chatbots continue to become more prevalent online, expect these risks to grow. As more and more data is created and stored within these systems, the risk of compromise or misuse will only continue to grow.
A Multi-Faceted Response
Preparing for cyber threats isn’t just about building systems that your cybersecurity team is aware of – it’s about empowering all employees with the skills and knowledge necessary to identify cyber threats.
By creating a workplace culture that considers cybersecurity a priority, organisations can embed practices that can help chatbots from being misused and repurposed for malicious intent. Having a cyber aware workforce is much like having a lock on a door – while bad actors will always try to barge through (and some may succeed), having an awareness of the risks can help to capture some threats early.
Having a cybersecurity plan is more than just awareness – it’s about asking the tough questions, like:
- If a cyber incident occurs, what protocols should the business adopt to respond and react?
- What needs to be done to keep chatbot data safe?
- What policies are in place to preserve the privacy and integrity of personal information?
- What do teams need to know, in order to be able to help the organisation meet their cybersecurity targets?
By being diligent, and planning for the future, cyber teams fill a vital role in protecting not only chatbot data, but also the customers that use it.
The Internet has changed a lot in the last twenty years – and how chatbots are treated and managed is just one example of the challenges that face workforces across the world. So the next time you enter data into a chatbot, take a moment to appreciate all the work that’s been done to ensure your experience is safe and secure. After all, who knows what threats lay around the dark corners of the web.
