AI in healthcare: navigating opportunities and challenges in digital communication

chatbot challenges

First off, AI can handle multiple queries at once, meaning customers don’t have to wait in long queues. It’s like having an extra team of customer service agents that never sleep. Plus, AI algorithms analyze past interactions and data to provide tailored answers to each customer. Once set up, these AI systems require less maintenance and can significantly reduce operational costs. As we know, we’re conversing with software fuelled by artificial intelligence, which brings forth a sense of loss of human touch in the conversations. The interactions could come off as cold and robotic, lacking personality and conversational flow.

Microsoft released a service that allowed different firms to develop their chatbots back in 2019. They gave different firms the tools needed to alleviate administrative tasks using chatbots, which helped Microsoft earn the top spot in the healthcare market. As per Juniper Research, AI can automate 73% of health admin tasks, and the adoption of AI chatbots could help the banking, healthcare and retail sector $11 billion annually by 2023. As artificial intelligence (AI) increasingly enters the mainstream, developers are facing important ethical questions about how to design AI chatbots.

This chatbot development would leverage sentiment analysis practices to train chatbots with more human-like capabilities. The focus of chatbots won’t be limited to providing effective response and understanding if the customer chat is going positive, neutral or negative and taking necessary corrective actions accordingly. As we discussed above, simple chatbots work on a list of pre-determined questions and provide a standard list of menu options to solve the anticipated queries users might have about their services. AI empowers chatbots to engage with the customers contextually by utilizing various tools to monitor visitors’ journey from google search or organic navigation path that got them here.

This means that Google Bard is more likely to be up-to-date on current events, while ChatGPT is more likely to be accurate in its responses to factual questions (AlZubi et al., 2022; Rahaman et al., 2023; Rudolph et al., 2023). Chatbots can deflect simple tasks and customer queries, but sometimes a human agent should be involved. With AI, bots can collect important information at the beginning of an interaction—using routing and intelligence to get the conversation to the best agent based on skill, availability, capacity, and issue priority. These seamless handoffs from chatbots to agents can help streamline service, save time, and enhance the customer experience. ChatGPT is a specific natural language processing (NLP) tool that uses generative AI.

Forbes conducted a study that predicted that 50 percent of all searches in the year 2021 would be voice-driven. Voice bots provide a seamless user experience which is important for business communications. Some chatbots on websites look like Chat GPT spams that users will, at all costs, avoid interacting with. This shows the need to focus on chatbots security features just as much as other aspects. However, there are many factors to consider for ensuring overall chatbot security.

  • In the context of remote patient monitoring, AI-driven chatbots excel at processing and interpreting the wealth of data garnered from wearable devices and smart home systems.
  • While chatbots are fantastic at answering FAQs and resolving common problems, they can fall short when it comes to more complex cases.
  • Indirect Prompt Injection (IPI) is another security vulnerability that is closely related to Prompt Injection.
  • They also act as study companions, offering explanations and clarifications on various subjects.
  • Similarly, in an educational setting, the deployment of chatbots may include collecting, analysing, and storing student data.
  • Students who choose that route expect greater flexibility, personalization and real-world relevance in their education.

You must have probably interacted with chatbots at some point in your life, either while booking a cab ride or ordering a coffee from a nearby café. Most of the websites and mobile apps have chatbots embedded with them, so they must have helped you in some way or the other. We can’t provide exact estimates of how much in-house or outsourced development costs, and most chatbot providers only give pricing details on sales calls.

Among them, ChatGPT and Google Bard are among the most profound AI-powered chatbots. It was first announced in November 2022 and is available to the general public. ChatGPT’s rival Google Bard chatbot, developed by Google AI, was first announced in May 2023. Both Google Bard and ChatGPT are sizable language model chatbots that undergo training on extensive datasets of text and code. They possess the ability to generate text, create diverse creative content, and provide informative answers to questions, although their accuracy may not always be perfect. The key difference is that Google Bard is trained on a dataset that includes text from the internet, while ChatGPT is trained on a dataset that includes text from books and articles.

So, people get bored when there is no response or delayed response from the other side. A chatbot needs a clear scope of the topic to get ready for the user’s answers. There is no satisfactory answer if the chatbot is being used at a broader level or for several topics.

Continuously monitor and improve chatbot performance

AI chatbots can offer a range of advantages for customer service, such as reducing costs and increasing efficiency, improving customer experience and loyalty, and collecting and analyzing data. However, the most recent advancements have propelled chatbots into critical roles related to patient engagement and emotional support services. This progression underscores the transformative potential of chatbots, including modern iterations like ChatGPT, to transcend their initial https://chat.openai.com/ role of providing information and actively participate in patient care. As these AI-driven conversational agents continue to evolve, their capacity to positively influence patient behavior and lifestyle choices becomes increasingly evident, reshaping the landscape of healthcare delivery and patient well-being. AI chatbots are software applications that use artificial intelligence (AI) and natural language processing (NLP) to simulate human conversations with customers.

Anthology created this AI-powered course-building tool that helps educators develop courses faster, thus embracing AI as a productivity tool to improve efficiencies and spend more time engaging learners. Perhaps most worrying is that current UK data privacy regulations allow individuals to request that their data be deleted from an organisation after a certain period. Whilst this may be possible using generative chatbots, the underlying algorithms of the technology will have already learned from the inputted data; thus true deletion of data may not be possible.

Frequent encounters with AI hallucinations can decrease students’ trust in AI as a reliable educational tool, and this distrust can extend to other digital learning resources and databases. In the context of integrating AI technologies into education, the issue of plagiarism emerges as a critical ethical concern (Teel et al., 2023). The facility of AI-powered tools such as ChatGPT may encourage students to misrepresent AI-generated outputs as their own, thereby compromising the integrity of their academic work. This issue is particularly paramount in educational ecosystems that emphasise outcomes or end goals, such as grades or qualifications, over the learning process. For example, all phases of the UK’s education systems have traditionally emphasised these quantifiable measures of academic success (Mansell, 2007). Moreover, there is a need for transparency about these biases and an ongoing dialogue about their implications.

Research questions

While many chatbots follow predetermined conversational paths, some employ personalized learning approaches tailored to individual student needs, incorporating experiential and collaborative learning principles. Challenges in chatbot development include insufficient training datasets, a lack of emphasis on usability heuristics, ethical concerns, evaluation methods, user attitudes, programming complexities, and data integration issues. The landscape of healthcare communication is undergoing a profound transformation in the digital age, and at the heart of this evolution are AI-powered chatbots. This mini-review delves into the role of AI chatbots in digital health, providing a detailed exploration of their applications, benefits, challenges, and future prospects. Our focus is on their versatile applications within healthcare, encompassing health information dissemination, appointment scheduling, medication management, remote patient monitoring, and emotional support services. However, it also addresses the significant challenges posed by the integration of AI tools into healthcare communication.

No use, distribution or reproduction is permitted which does not comply with these terms. Additionally, deploying advanced plagiarism detection software capable of identifying AI-generated text is a practical step that can be implemented. However, as AI technologies evolve, so must our detection methodologies, necessitating continuous advancements in this field. Software such as Turnitin cannot detect essays written by AI because the text is originally generated and not copied. The author remains doubtful that development’s plagiarism detection software will ever be one step ahead of AI technologies and be free of reporting false-positives. OpenAI, the creator of ChatGPT, released a free detection tool on February 1 to help educators and others distinguish if a text was written by a human or a machine.

The complex nature of these systems frequently shrouds the rationale behind their decisions, presenting a substantial barrier to cultivating trust in their application. Another big challenge that comes with customizing and adjusting chatbots behavior is understanding the limits of Natural Language Processing (NLP). While it is the backbone of any chatbot – if gone too far it may be as good as dreaming out an elephant in a gulp of a cloud looking exasperated upside down. In other words – it may end up being as incomprehensible as any cat-sitting-on-keyboard sessions. This makes the whole process of independently developing chatbots even more complex.

Enhancing the chatbot’s NLP capabilities enables it to understand a broader range of customer queries and respond appropriately. 6) Integration with Third-Party ServicesChatbots are increasingly expected to go beyond simple informational interactions and perform tasks like making reservations, accessing external databases, or interacting with other services. The challenge here lies in seamlessly integrating the chatbot with a diverse array of third-party APIs and services. Each external service may have its unique data structures, authentication methods, and error-handling processes. Ensuring a smooth flow of information and actions between the chatbot and these services without compromising user experience is a complex task.

What are the challenges of AI chatbots?

Implementing AI chatbots comes with challenges such as the need for extensive training data to ensure accurate natural language processing. There is also the challenge of addressing potential ethical concerns and ensuring the chatbot's responses align with company values and policies.

Later in 2001 ActiveBuddy, Inc. developed the chatbot SmarterChild that operated on instant messaging platforms such as AOL Instant Messenger and MSN Messenger (Hoffer et al., 2001). SmarterChild was a chatbot that could carry on conversations with users about a variety of topics. It was also able to learn from its interactions with users, which made it more and more sophisticated over time. In 2011 Apple introduced Siri as a voice-activated personal assistant for its iPhone (Aron, 2011).

A noteworthy example is TytoCare’s telehealth platform, where AI-driven chatbots guide patients through self-examination procedures during telemedicine consultations, ensuring the integrity of collected data (9). Appointment scheduling and management represent another vital area where chatbots streamline processes. Patients can easily book appointments, receive reminders, and even reschedule appointments through chatbot interactions (6).

Chatbots will behave more in a human-like manner.

Consequently, a substantial body of academic literature is dedicated to investigating the role of AI chatbots in education, their potential benefits, and threats. For instance, DeepMind Health, a pioneering initiative backed by Google, has introduced Streams, a mobile tool infused with AI capabilities, including chatbots. Streams represents a departure from traditional patient management systems, harnessing advanced machine learning algorithms to enable swift evaluation of patient results. This immediacy empowers healthcare providers to promptly identify patients at elevated risk, facilitating timely interventions that can be pivotal in determining patient outcomes. Customers today expect a personalized experience that caters to their unique needs and preferences. Designers create chatbots to provide quick responses based on pre-programmed rules and scripts, but they lack the ability to understand and respond to customers’ needs.

This approach allows chatbots to expand their knowledge base and provide more accurate and relevant responses to customer queries. There exists a concept of natural language processing or Neuro-linguistic programming with which, if the chatbot is programmed, it can interpret, recognize, and understand the queries made by any user for the upcoming users. All this is a part of Machine learning and Artificial intelligence combined, and it can be improved with the help of adept AI and ML developers. For example, one user might prefer concise answers, while another may appreciate a more detailed explanation for the same query. The challenge is to make the chatbot capable of adapting its responses to suit the individuality of each user.Overcoming the challenge of personalization involves creating robust user profiling mechanisms. By employing machine learning algorithms, developers can analyze user behavior, language nuances, and preferences to build detailed user profiles.

Data using Woebot, she says, has been published in peer-reviewed scientific journals. And some of its applications, including for post-partum depression and substance use disorder, are part of ongoing clinical research studies. The company continues to test its products’ effectiveness in addressing mental health conditions for things like post-partum depression, or substance use disorder. Skeptics point to instances where computers misunderstood users, and generated potentially damaging messages. Maybe the most controversial applications of AI in the therapy realm are the chatbots that interact directly with patients like Chukurah Ali. “The hype and promise is way ahead of the research that shows its effectiveness,” says Serife Tekin, a philosophy professor and researcher in mental health ethics at the University of Texas San Antonio.

It requires vast amounts of data and effort to train chatbots to handle the myriad of issues customers may face. Chatbots often forget details from earlier in the interaction, leading to confusion and providing irrelevant responses. Technologies developed by artificial intelligence development companies like deep gaining knowledge of and neural networks, allow for extra sophisticated capabilities.

chatbot challenges

However, there are potential difficulties in fully replicating the human educator experience with chatbots. While they can provide customized instruction, chatbots may not match human instructors’ emotional support and mentorship. Understanding the importance of human engagement and expertise in education is crucial. They offer students guidance, motivation, and emotional support—elements that AI cannot completely replicate. It is evident that chatbot technology has a significant impact on overall learning outcomes. Specifically, chatbots have demonstrated significant enhancements in learning achievement, explicit reasoning, and knowledge retention.

A ChatGPT user can also snap a picture of a landmark while traveling and have a live conversation with the bot about what makes the location interesting. Meta does have a general-purpose Llama LLM, with more than 400 billion parameters. But a white paper published with the launch of the Meta AI chatbot notes there are smaller 7 billion- and 13 billion-parameter models, among others.

However, as AI tools like ChatGPT evolve, developers may find ways to reduce their risks. Organizations that want to invest in a generative AI tool should understand how different vendors train their products and whether they apply safeguards to reduce risks of bias. If organizations plan to train a tool themselves, they should also do their best to keep biased information out of their training data. In conclusion, privacy considerations, although challenging, are manageable through policy and legislation.

  • That is how Ali found herself on a new frontier of technology and mental health.
  • AI chatbots are like super-intelligent sidekicks working round-the-clock for you.
  • Each enterprise has to focus on encrypting its channels so that no data is leaked through its mediums; Especially when dealing with sensitive data.
  • AI-powered chatbots can be equipped with NLP — Natural Language Processing tools, which can help determine the need behind any inquiry.
  • If you feed your chatbot an abundance of poorly structured data, it works against the desired outcome and makes your chatbots inefficient.
  • No matter how well your chatbot is trained and designed, there will always be cases when the human touch is necessary.

A chatbot development company considers all models, from generative to retrieval-based, to create an intelligent and interactive solution for your business. However, one of NLP’s limitations is its difficulty adapting to different languages and colloquial and dialects terms. In the healthcare industry, chatbots can assist with patient monitoring, provide personalized health recommendations, and even diagnose conditions. Chatbots can provide 24/7 customer support and assist with financial planning in the financial sector. Developers and software development companies should develop an improved memory for chatbots to provide better support and a more human connection.

In systems that heavily emphasise outcomes, designing assessments that evaluate students’ understanding and encourage original thinking, creativity, and skills currently beyond AI’s reach becomes essential. You can foun additiona information about ai customer service and artificial intelligence and NLP. King (2023, p. 3) encourages universities to design assignments that minimise the potential of cheating through platforms such as ChatGPT by incorporating a variety of assessment methods that go beyond traditional essay writing. For example, they could ‘incorporate oral presentations, group projects, and hands-on activities that require students to demonstrate their knowledge and skills in a more interactive and engaging way’.

If customers perceive your chatbot as unhelpful or as a barrier to support, it can lead to feelings of disappointment and detachment. This can lead to customer dissatisfaction and a poor customer service experience. As a result of these limitations, customers who reach out to a chatbot with a complex problem may end up stuck in an unproductive interaction that reaches no resolution.

Let’s explore more about the benefits of using AI chatbots and the problems AI chatbots solve. And you’ll be amazed to know that 88% of the customers had at least one conversation with the chatbot within the past year. These powerful digital assistants are revolutionizing how businesses address and resolve issues, allowing them to stay ahead of the curve and adapt to the rapidly evolving market. In order to protect against this threat, it is necessary to constantly monitor data quality and validate input data.

The Current Scenario of AI Chatbots

Note down any time the automation does something unexpected and see how you can work on it. This technology works best when you let it learn for some time before releasing it to your customers. This method is used for testing the efficiency of the conversational logic of chatbots. Here a close group of testers conduct manual testing by acting as users and checking the bot for all the possible slots. It’s important to note that some papers raise concerns about excessive reliance on AI-generated information, potentially leading to a negative impact on student’s critical thinking and problem-solving skills (Kasneci et al., 2023). For instance, if students consistently receive solutions or information effortlessly through AI assistance, they might not engage deeply in understanding the topic.

The fewer the parameters, the more efficient and customized an LLM can be without placing additional strains on server CPU cycles. The top chart in Figure 1 demonstrates four categories of use and disclosure of PHI under HIPAA. While AI may not fully simulate one-on-one individual counseling, its proponents say there are plenty of other existing and future uses where it could be used to support or improve human counseling. Tekin says there’s a risk that teenagers, for example, might attempt AI-driven therapy, find it lacking, then refuse the real thing with a human being. “My worry is they will turn away from other mental health interventions saying, ‘Oh well, I already tried this and it didn’t work,’ ” she says.

What are the challenges in responsible AI?

Our work discusses reasons for this lack of impact and clusters them into five areas: (1) the abstract nature of RAI guidelines, (2) the problem of selecting and reconciling values, (3) the difficulty of operationalising RAI success metrics, (4) the fragmentation of the AI pipeline, and (5) the lack of internal …

They’re like your own personal customer service team, able to offer tailored care to a lot of clients simultaneously. Rule-based chatbots (or chat flows) can take care of the common questions that can be answered within one message. AI bots, on the other hand, can handle customer queries that have follow-up questions and require AI and natural language understanding algorithms to decipher the intent. Many people wrongly assume that chatbots need to automate the customer support process entirely.

Learn about the current state of cybersecurity and our recommended best practices for a secure Zendesk Suite experience. Platforms may also collect and store sensitive details that bad actors could access or leak, so organizations must take steps to minimize the risk of AI breaches. The answer is integrating the responsible use of AI, which is why Anthology came out with the AI Policy Framework.

Measure and implement effective and well-planned strategies before presenting your audience with your Chatbot. Chatbots are incredibly rigid in how they perceive data and what they deliver. In the case of chatbots, the data is in the form of Natural Language Processing (NLP). NLP is a mixture of linguistics and computer science that attempts to make sense of text understandably. Coming back to chatbots, think of them as serving a much bigger purpose and one that needs to be approached with a purposeful and long-term strategy to be successful. That frequently necessitates the creation of a dedicated team to be in charge of monitoring trial results and enhancing performance over time in a learn-and-test approach.

chatbot challenges

As technology continues to advance, AI-powered educational chatbots are expected to become more sophisticated, providing accurate information and offering even more individualized and engaging learning experiences. They are anticipated to engage with humans using voice recognition, comprehend human emotions, and navigate social interactions. This includes activities such as establishing educational objectives, developing teaching methods and curricula, and conducting assessments (Latif et al., 2023). Considering Microsoft’s extensive integration efforts of ChatGPT into its products (Rudolph et al., 2023; Warren, 2023), it is likely that ChatGPT will become widespread soon.

In short, an engaging chatbot personality will help bridge the gap between human and bot-powered customer service. Ultimately, the lack of human connection with chatbots creates a gap in meeting customer needs. It’s why chatbots are one of the fastest-growing brand communication channels, used by around 80% of businesses worldwide. One technology that has gained significant popularity in recent years is the customer service chatbot. In the realm of AI-driven communication, a fundamental challenge revolves around elucidating the models’ decision-making processes, a challenge often denoted as the “black box” problem (25).

It can help create a more personalized experience and build stronger customer relationships. From generative to retrieval-based models, a chatbot development company weighs all models to create an intelligent and interactive solution for your business. However, there are some limitations to NLP that it has some difficulties in not only adapting to different languages but also, different dialects and colloquial terms.

chatbot challenges

One way to add emotions to chatbots is by using emoticons or emojis in the responses. Emojis can convey emotions like happiness, sadness, anger, or excitement, making the conversation more engaging and humanlike. Programmers program these chatbots to recognize and respond to emotions, thereby making them more empathetic and responsive. Also, businesses must focus on the security features of their chatbot solutions besides other aspects like features. Additionally, you need to ensure that the chatbot is secure so that no one can access your chats.

However, they also pose some challenges and risks that need to be addressed before implementing them. In this article, we will explore some of the common issues and pitfalls of using password reset chatbot and automation in technical support, and how to overcome them. Chatbots are going to focus on becoming more conversational for increasing communication efficiency, as this is the next step to improve user experience.

If faculty can embrace AI as a productivity benefit, they can more readily present it as a future advantage for students as they enter the workforce. This is an exciting time; we need to keep an open mind about AI and stay current with the technology while still being responsible. The first is using AI to help a professor simplify or improve the rudimentary aspects of their job so they have more time with students.

Tools to use and chatbot challenges: How the marketing world is navigating AI – Marketing Brew

Tools to use and chatbot challenges: How the marketing world is navigating AI.

Posted: Mon, 04 Mar 2024 08:00:00 GMT [source]

The widespread adoption of conversational AI could bring efficiency and improved customer experience to the retail world, addressing everything from supply-chain woes to onboarding issues. But despite the large number of AI offerings out there, the rapid evolution of retail chatbots hasn’t come without challenges. The chatbot uses artificial intelligence to create content that responds to users’ prompts. People can type their questions into a text box and engage in conversations with the bot. Its responses are based on a database of digital books, online writings and other media. If two competing bidders use the same AI tool to develop their proposals, there is a chance that the proposals will appear similar.

How can chatbots be improved?

  1. 1 Analyze your chatbot data. The first step to improve your chatbot performance is to analyze the data you collect from your interactions with customers.
  2. 2 Optimize your chatbot design.
  3. 3 Train your chatbot regularly.
  4. 4 Measure your chatbot impact.
  5. 5 Update your chatbot frequently.
  6. 6 Experiment with your chatbot.

Drawing from extensive systematic literature reviews, as summarized in Table 1, AI chatbots possess the potential to profoundly influence diverse aspects of education. However, it is essential to address concerns regarding the irrational use of technology and the challenges that education systems encounter while striving to harness its capacity and make the best use of it. Though customer service chatbots may require an investment upfront, they can help you save money over time. Chatbots can handle simple tasks, deflect tickets, and intelligently route and triage conversations to the right place quickly. This allows you to serve more customers without having to hire more agents.

The user doesn’t really like to deal with answering machine (which chatbot basically is). But the most common is selecting several manners of conversing – more formal, informal or flowery or excessively minimalist. However, no matter how mighty and reaching chatbots are – they are just sets of ones and zeroes which need to be taken care off. If not – be prepared to utter “mistakes were made” while going through a door. It definitely is a great idea to involve chatbots in your digital marketing, yielding efficient results in less amount of time. But creating one that meets all the expectations of your organization can be pretty challenging.

The issue with this solution is that humans do not necessarily interact in a defined order. For this chatbot, developers need to provide intelligent slot filling to effectively store the regular users’ preferences and maintain the bot’s memory. AI bots won’t replace customer service agents—they are a tool that enhances the experiences of both businesses and consumers. Customers will always want to know they can talk to another human, especially regarding issues that benefit from a personal touch.

Chatbots for mental health pose new challenges for US regulatory framework – News-Medical.Net

Chatbots for mental health pose new challenges for US regulatory framework.

Posted: Wed, 01 May 2024 07:00:00 GMT [source]

Yet approximately one-third said they have never received training in public welfare – not during their education, and not during their career. Researchers in one 2018 study interviewed over 50 engineering faculty and documented hesitancy – and sometimes even outright resistance – toward incorporating public welfare issues into their engineering classes. More than a quarter of professors they interviewed saw ethics and societal impacts as outside “real” engineering work. A user would be able to have back-and-forth conversation with ChatGPT, ask it for facts during a dinnertime debate, or have it handle things such as a bedtime story for children.

The best alternative is to combine both the methods to insure that your users are being served better. Your AI chatbot should collect only the visitors’ necessary information and transmit it securely over the internet. Additionally, you need to invest in your AI chatbot to make it hack-proof as well.

They can also understand intent, sentiment and language through constant learning. They function on machine learning technology, through which they can constantly learn and improve. They self-improve from the interactions chatbot challenges they have with various users as well. AI chatbots can be considered smart chatbots as they’re built with advanced technology and have the potential to provide excellent user experience, help, and ease to their users.

The author argues that oral presentations, such as viva voices and group projects, could be an effective assessment method to discourage plagiarism and promote learning outcomes. In other words, oral presentations must solely be done by a human, whereas the benefits of AI can still be realised to aid student preparation. Nevertheless, this approach may be considered a short-term solution to the constantly evolving AI technology, especially in the realms of online presentations and interviews. De Vries (2020) argues that deep fakes can blur the lines between what is fact and fiction by generating fake video footage, pictures and sounds. Similarly, AI-powered platforms such as AI Apply can quickly transcribe real-time questions posed during online presentations, formulate a rapid answer, and then vocalise it as if it were the student (Fitria, 2023). However, the author argues that this is a challenge that the wider society will likewise have to grapple with, as there will be implications for political deception, identity scams, and extortion (De Vries, 2020).

Natural language processing permits the chatbot to interpret human language input by means of analyzing syntax, detecting entities, and figuring out intent. The use of machine learning strategies like supervised studying, reinforcement gaining knowledge of, and deep learning is to build additives like purpose classifiers and conversation managers that may enhance mechanically. Knowledge bases store statistics, policies, and facts the chatbot can question to generate relevant responses. Another solution to limited responses is to incorporate machine learning into chatbot development. Machine learning enables chatbots to learn and improve their responses by analyzing customer interactions.

The issue becomes more pronounced, particularly for young students, who may need to be made aware of the implications of their digital footprints and the need for digital privacy. Using the Clearing example, it is reasonable to assume that several individuals under 18 would provide information through this technology. In commercial applications, chatbots can improve customer experience and provide smooth interactions, making it easier for customers to engage with an organisation and providing lower-cost customer service than live agents (Williams, 2023). However, the enhanced personalised experience is only possible because of the gathering of ‘big data’, such as tracking behaviour, habits, and patterns, and analysing them against historical customer activity. It is, therefore, important to investigate the concerns of using chatbots in education to ensure safe and ethical use. This article briefly introduces the ethical implications of using platforms such as ChatGPT in education.

What are chatbots’ weaknesses?

Chatbots offer tremendous benefits, but they also have potential disadvantages. These perceived disadvantages include: A limited ability to understand complex input. A lack of empathy. Set-up effort.

What are the 4 main problems AI can solve?

  • Healthcare diagnosis and treatment.
  • Customer service and engagement.
  • Cybersecurity threat detection.
  • Autonomous vehicles.
  • Educational personalization.
  • Predictive maintenance in the industry.
  • Breaks communication barrier.
  • AI in robotics.

Why is chatbot a threat?

API vulnerabilities present another significant security risk for chatbots, particularly when these interfaces are used to share data with other systems and applications. Exploiting API vulnerabilities can give attackers unauthorized access to sensitive information such as customer data, passwords, and more.