#best ai chatbot development company

[sffgtrhyjhmnzdt]

Empower Your WhatsApp Presence: Top Chatbot Service Providers 

In the ever-evolving landscape of digital communication, WhatsApp stands as a ubiquitous platform connecting billions of users worldwide. Leveraging the power of chatbots on WhatsApp can revolutionize how businesses engage with their audience, providing personalized interactions, streamlined customer service, and enhanced operational efficiency. Among the myriad of service providers, VoxDigital emerges as a frontrunner, offering cutting-edge solutions tailored to elevate your WhatsApp presence. Let's explore the top best AI chatbot customer services in USA providers within renowned for their innovation, reliability, and commitment to delivering exceptional user experiences.

VoxDigital's flagship chatbot solution, empowers businesses to create intelligent conversational experiences on WhatsApp effortlessly. Built on advanced AI technology, excels in natural language understanding, enabling seamless interactions with users. With an intuitive interface and robust feature set, businesses can design custom chatbots, automate responses, and analyze conversation metrics to optimize engagement and satisfaction levels.

VoxDigital's conversational flow builder, simplifies the process of designing and deploying WhatsApp chatbots. Featuring a visual drag-and-drop interface, the best AI chatbot development company in India enables businesses to create dynamic conversational flows, define decision trees, and incorporate multimedia elements seamlessly. Whether it's lead generation, customer support, or sales automation, equips businesses with the tools to craft engaging chatbot experiences tailored to their objectives.

Analytics platform provides actionable insights into chatbot performance and user behavior on WhatsApp. With best AI chatbot software providers in the USA comprehensive dashboards and reporting tools, businesses can track key metrics, monitor conversation trends, and gain valuable insights to optimize their chatbot strategy continuously. By leveraging VoxInsights, businesses can make data-driven decisions to enhance user engagement and drive business outcomes effectively.

VoxDigital's customer support service, provides businesses with dedicated assistance and expertise in deploying and managing WhatsApp chatbots. From initial setup and configuration to ongoing maintenance and optimization, ensures that businesses receive timely support and guidance at every stage of their chatbot journey. With VoxSupport's proactive monitoring and responsive service, businesses can rest assured that their chatbots operate smoothly and deliver value consistently.

Best ai chatbot software providers in India, offering a comprehensive suite of solutions and services to empower businesses in their digital transformation journey. By partnering with VoxDigital's ecosystem of chatbot service providers, businesses can unlock the full potential of WhatsApp as a powerful platform for customer engagement, lead generation, and business growth. Whether it's through intelligent automation, insightful analytics, or seamless integration, VoxDigital enables businesses to elevate their WhatsApp presence and stay ahead in today's competitive landscape.

[aidevelop]

"Scalable AI Chatbot Development for Businesses of All Sizes"

Our scalable AI chatbot solutions cater to startups, SMEs, and large enterprises. Empower your business with automated Generative AI Chatbot Solutions that can grow with your needs and deliver consistent customer experiences across platforms.

[jcmarchi]

Bridging code and conscience: UMD's quest for ethical and inclusive AI

New Post has been published on https://thedigitalinsider.com/bridging-code-and-conscience-umds-quest-for-ethical-and-inclusive-ai/

Bridging code and conscience: UMD's quest for ethical and inclusive AI

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As artificial intelligence systems increasingly permeate critical decision-making processes in our everyday lives, the integration of ethical frameworks into AI development is becoming a research priority. At the University of Maryland (UMD), interdisciplinary teams tackle the complex interplay between normative reasoning, machine learning algorithms, and socio-technical systems. 

In a recent interview with Artificial Intelligence News, postdoctoral researchers Ilaria Canavotto and Vaishnav Kameswaran combine expertise in philosophy, computer science, and human-computer interaction to address pressing challenges in AI ethics. Their work spans the theoretical foundations of embedding ethical principles into AI architectures and the practical implications of AI deployment in high-stakes domains such as employment.

Normative understanding of AI systems

Ilaria Canavotto, a researcher at UMD’s Values-Centered Artificial Intelligence (VCAI) initiative, is affiliated with the Institute for Advanced Computer Studies and the Philosophy Department. She is tackling a fundamental question: How can we imbue AI systems with normative understanding? As AI increasingly influences decisions that impact human rights and well-being, systems have to comprehend ethical and legal norms.

“The question that I investigate is, how do we get this kind of information, this normative understanding of the world, into a machine that could be a robot, a chatbot, anything like that?” Canavotto says.

Her research combines two approaches:

Top-down approach: This traditional method involves explicitly programming rules and norms into the system. However, Canavotto points out, “It’s just impossible to write them down as easily. There are always new situations that come up.”

Bottom-up approach: A newer method that uses machine learning to extract rules from data. While more flexible, it lacks transparency: “The problem with this approach is that we don’t really know what the system learns, and it’s very difficult to explain its decision,” Canavotto notes.

Canavotto and her colleagues, Jeff Horty and Eric Pacuit, are developing a hybrid approach to combine the best of both approaches. They aim to create AI systems that can learn rules from data while maintaining explainable decision-making processes grounded in legal and normative reasoning.

“[Our] approach […] is based on a field that is called artificial intelligence and law. So, in this field, they developed algorithms to extract information from the data. So we would like to generalise some of these algorithms and then have a system that can more generally extract information grounded in legal reasoning and normative reasoning,” she explains.

AI’s impact on hiring practices and disability inclusion

While Canavotto focuses on the theoretical foundations, Vaishnav Kameswaran, affiliated with UMD’s NSF Institute for Trustworthy AI and Law and Society, examines AI’s real-world implications, particularly its impact on people with disabilities.

Kameswaran’s research looks into the use of AI in hiring processes, uncovering how systems can inadvertently discriminate against candidates with disabilities. He explains, “We’ve been working to… open up the black box a little, try to understand what these algorithms do on the back end, and how they begin to assess candidates.”

His findings reveal that many AI-driven hiring platforms rely heavily on normative behavioural cues, such as eye contact and facial expressions, to assess candidates. This approach can significantly disadvantage individuals with specific disabilities. For instance, visually impaired candidates may struggle with maintaining eye contact, a signal that AI systems often interpret as lack of engagement.

“By focusing on some of those qualities and assessing candidates based on those qualities, these platforms tend to exacerbate existing social inequalities,” Kameswaran warns. He argues that this trend could further marginalise people with disabilities in the workforce, a group already facing significant employment challenges.

The broader ethical landscape

Both researchers emphasise that the ethical concerns surrounding AI extend far beyond their specific areas of study. They touch on several key issues:

Data privacy and consent: The researchers highlight the inadequacy of current consent mechanisms, especially regarding data collection for AI training. Kameswaran cites examples from his work in India, where vulnerable populations unknowingly surrendered extensive personal data to AI-driven loan platforms during the COVID-19 pandemic.

Transparency and explainability: Both researchers stress the importance of understanding how AI systems make decisions, especially when these decisions significantly impact people’s lives.

Societal attitudes and biases: Kameswaran points out that technical solutions alone cannot solve discrimination issues. There’s a need for broader societal changes in attitudes towards marginalised groups, including people with disabilities.

Interdisciplinary collaboration: The researchers’ work at UMD exemplifies the importance of cooperation between philosophy, computer science, and other disciplines in addressing AI ethics.

Looking ahead: solutions and challenges

While the challenges are significant, both researchers are working towards solutions:

Canavotto’s hybrid approach to normative AI could lead to more ethically-aware and explainable AI systems.

Kameswaran suggests developing audit tools for advocacy groups to assess AI hiring platforms for potential discrimination.

Both emphasise the need for policy changes, such as updating the Americans with Disabilities Act to address AI-related discrimination.

However, they also acknowledge the complexity of the issues. As Kameswaran notes, “Unfortunately, I don’t think that a technical solution to training AI with certain kinds of data and auditing tools is in itself going to solve a problem. So it requires a multi-pronged approach.”

A key takeaway from the researchers’ work is the need for greater public awareness about AI’s impact on our lives. People need to know how much data they share or how it’s being used. As Canavotto points out, companies often have an incentive to obscure this information, defining them as “Companies that try to tell you my service is going to be better for you if you give me the data.”

The researchers argue that much more needs to be done to educate the public and hold companies accountable. Ultimately, Canavotto and Kameswaran’s interdisciplinary approach, combining philosophical inquiry with practical application, is a path forward in the right direction, ensuring that AI systems are powerful but also ethical and equitable.

See also: Regulations to help or hinder: Cloudflare’s take

Want to learn more about AI and big data from industry leaders? Check out AI & Big Data Expo taking place in Amsterdam, California, and London. The comprehensive event is co-located with other leading events including Intelligent Automation Conference, BlockX, Digital Transformation Week, and Cyber Security & Cloud Expo.

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Tags: ai, artificial intelligence, ethics, research, Society

[techavtar]

[techminddevelopers]

The Rise of AI-Powered Customer Service: Transforming Businesses in 2024

Introduction

In today’s competitive landscape, customer experience is crucial. Businesses are increasingly turning to AI to enhance customer service. At Tech Mind Developers, we recognize AI’s potential to create seamless, efficient, and personalized customer interactions. This blog explores how AI-powered customer service is revolutionizing industries and how your business can benefit.

Key Technologies in AI-Powered Customer Service

1. Chatbots and Virtual Assistants:

24/7 Availability: AI chatbots handle customer queries round-the-clock, providing instant responses.

Scalability: Manage multiple interactions simultaneously, ensuring no customer is left unattended.

Natural Language Processing (NLP): Understand and respond to customer queries in a human-like manner.

2. AI-Driven Analytics:

Customer Insights: Analyze data to uncover trends and preferences.

Predictive Analytics: Anticipate customer behavior to proactively address issues.

3. Voice Recognition and AI-Powered IVR Systems:

Enhanced Call Routing: Accurately route calls based on customer needs.

Voice Biometrics: Authenticate customers through voice recognition, enhancing security.

Benefits of AI-Powered Customer Service

Improved Efficiency: AI handles routine inquiries, allowing human agents to focus on complex issues, enhancing overall efficiency.

Enhanced Customer Experience: Instant responses and personalized interactions ensure customers feel valued, leading to higher satisfaction rates.

Data-Driven Decision Making: AI provides actionable insights from customer data, enabling continuous improvement of service offerings.

Cost Savings: Automating processes reduces the need for large support teams, resulting in significant cost savings.

Real-World Applications

E-commerce: AI chatbots assist with product inquiries, order tracking, and returns, enhancing the shopping experience.

Banking and Finance: Financial institutions use AI-driven chatbots for account information, transaction details, and fraud detection.

Healthcare: AI chatbots assist patients with appointment scheduling and medical inquiries.

Telecommunications: AI helps troubleshoot technical issues and manage billing inquiries.

How Tech Mind Developers Can Help

At Tech Mind Developers, we specialize in integrating AI solutions into customer service frameworks. Our experts design and deploy AI-powered chatbots, analytics tools, and voice recognition systems tailored to your needs. Partner with us to ensure your customer service is efficient, cost-effective, and a key differentiator in your industry.

Conclusion

AI-powered customer service is transforming how businesses interact with customers. By embracing AI, companies can deliver superior experiences, streamline operations, and gain a competitive edge. At Tech Mind Developers, we’re committed to helping you harness AI’s power to revolutionize your customer service and drive your business forward.

For more information on implementing AI solutions, contact us at info@techminddevelopers.com or visit our website. Let us help you turn your digital aspirations into tangible successes.

#ai #customerservice #artificialintelligence #chatbots #virtualassistants #customerexperience #businessgrowth #predictiveanalytics #voicerecognition #techminddevelopers #ecommerce #banking #healthcare #telecommunications #digitaltransformation #innovativetechnology #costefficiency

[dziretechnologies]

Best Chatbot AI Development Company

Dzire Technologies stands out as the best Chatbot AI Development Company, delivering cutting-edge AI solutions that redefine industries. Our expertise spans predictive modeling, computer vision, GENAI applications, conversational chatbots, LLM integration, and business consulting tailored to the digital age. We offer building ai chatbot solution, analytical solutions, ai consulting, conversational chatbot etc.

[perfectiongeeks]

VISUAL CHATGPT: The Next Frontier Of Conversational AI

A conversational AI model called Visual Chatgpt merges natural language processing and computer vision to deliver a more complicated and engaging chatbot experience. There are a variety of potential uses for visual chat, including creating and modifying illustrations that might not be available online. It can remove objects from photos, modify the background coloring, and provide more precise AI descriptions of uploaded photographs. Visual foundation models play a vital role in the functioning of visual communication, allowing computer vision to decipher visual data. VFM models typically consist of deep-learning neural webs trained on huge datasets of labeled images or videotapes and can recognize objects, faces, emotions, and other visual elements of images.

Visit us:

[wordsystech]

Developing a Chatbot from Scratch: A Hands-On Approach

[probablyasocialecologist]

An increasing number of Silicon Valley investors and Wall Street analysts are starting to ring the alarm bells over the countless billions of dollars being invested in AI, an overconfidence they warn could result in a massive bubble. As the Washington Post reports, investment bankers are singing a dramatically different tune than last year, a period marked by tremendous hype surrounding AI, and are instead starting to become wary of Big Tech's ability to actually turn the tech into a profitable business. "Despite its expensive price tag, the technology is nowhere near where it needs to be in order to be useful," Goldman Sach's most senior stock analyst Jim Covello wrote in a report last month. "Overbuilding things the world doesn’t have use for, or is not ready for, typically ends badly."

[...]

According to Barclays analysts, investors are expected to pour $60 billion a year into developing AI models, enough to develop 12,000 products roughly the size of OpenAI's ChatGPT. But whether the world needs 12,000 ChatGPT chatbots remains dubious at best. "We do expect lots of new services... but probably not 12,000 of them," Barclays analysts wrote in a note, as quoted by the WaPo. "We sense that Wall Street is growing increasingly skeptical." For quite some time now, experts have voiced concerns over a growing AI bubble, comparing it to the dot-com crisis of the late 1990s. "Capital continues to pour into the AI sector with very little attention being paid to company fundamentals," tech stock analyst Richard Windsor wrote in a March research note, "in a sure sign that when the music stops there will not be many chairs available." "This is precisely what happened with the Internet in 1999, autonomous driving in 2017, and now generative AI in 2024," he added.

27 July 2024

[aidevelop]

Advanced Generative AI Chatbot Solutions for Personalized Customer Journeys

Leverage Build AI Chatbots technology to deliver tailored experiences for every customer, creating unique engagement strategies that adapt to individual preferences and behaviors.

[jcmarchi]

How Enterprise SaaS Companies Can Thrive in an AI-Driven World

New Post has been published on https://thedigitalinsider.com/how-enterprise-saas-companies-can-thrive-in-an-ai-driven-world/

How Enterprise SaaS Companies Can Thrive in an AI-Driven World

AI continues to dominate conversations surrounding modern knowledge work, weaving itself into the everyday processes of countless industries. As businesses continue to find utility in AI, sentiment towards it hovers somewhere between cautious optimism and outright skepticism.

Within the business world, many are seeing the technology’s usefulness while also grappling with its potential to alter the way many job roles function. It appears the fear that AI will wholly replace or eliminate jobs has largely faded and has been replaced by change fatigue; workers are being asked to make the most of AI to unlock its potential, and that is upending long-established positions.

SaaS companies are specifically under mounting pressure to stay competitive as AI continues to transform how systems function within organizations. By embracing AI, however, enterprise SaaS companies can leverage what they do best while supercharging their output to offer clients the best of both worlds.

Where AI Poses a Threat to SaaS

As AI becomes more ingrained in business, it’s changing how companies deploy and engage with SaaS platforms. Many SaaS companies are now asking: How will my business be affected by the rise of AI?

There’s no definitive answer, but there are some clues to help inform a business’s long-term viability. The things AI does well —  report generation, content generation, insight gathering, and more — can be a threat to SaaS platforms that focus on those outputs.

Broadly speaking, though, the biggest fear surrounding AI isn’t necessarily on the macro level but rather on the individual worker level. Companies will still need SaaS platforms to tackle a number of business cases, but certain roles that focus on AI’s core competencies may be at risk of augmentation. That’s not to say these jobs will be eliminated entirely, but there may be an increased focus on leveraging AI to maximize productivity and value, and therefore an increased pressure on these employees to learn, understand, and incorporate AI into their daily work.

Of course, with AI’s exponential growth and adoption, it’s impossible to say what the next five years of development will mean for SaaS companies. Analyzing risk means understanding a business’ strengths and comparing them with the areas in which AI excels. What’s clear is that AI is a powerful tool, and the platforms and workers who harness it the most effectively will be better off in the long run.

Why AI Can’t Replace SaaS Platforms

One of the more interesting applications of AI is its ability to write code. Business leaders have long theorized that AI could generate the code needed to create SaaS solutions, but when you spell it out, it feels a bit like science fiction: a business sees a software need, describes the product to an AI engine and voila, you have a custom-built SaaS platform.

Unfortunately (or fortunately), we’re not much closer to that reality now than we were 30 years ago. The technical skill required to create the complex systems that underpin SaaS platforms is far beyond what generative AI can conjure and will still require human input for the foreseeable future.

SaaS providers contain deep domain expertise that businesses rely on. If businesses could describe a SaaS platform in enough detail to where AI could generate software around it, they may not need a SaaS vendor in the first place. Understanding the ins and outs of their particular industry is key to SaaS success.

Knowing an industry is big, but knowing a product is even bigger. SaaS platforms understand their product better than anybody, and their robust customer relationships mean they understand their clients’ use cases better than any technology as well. One of the keys to long-term SaaS viability is the ability to know how a client can use their product to maximize its efficacy for their business.

Finally, SaaS platforms rely on established data ecosystems that make them indispensable for their clients. These ecosystems work to conform to industry standard data protocols and aid in data governance and security. They also help enable integrations with other platforms and provide a consistent data language that helps build scalable solutions.

How Embracing AI Gives SaaS Platforms the Edge

Taking the long view, it’s clear that AI isn’t a replacement for SaaS platforms but a tool to supercharge performance. The platforms that understand how best to integrate this technology will distinguish themselves in a crowded field. As AI continues to evolve, these capabilities are not just going to be differentiation points but table stakes for all SaaS platforms.

Integrating AI-driven features like robust, on-demand insights and enriched report generation gives clients the ability to turn raw data into something actionable the moment they need it. Reducing the lag between data collection and implementation is a major advantage for agile businesses.

AI is also excellent at enabling personalization at scale. AI algorithms can analyze vast amounts of user behavioral data and preferences to deliver highly tailored and customized experiences. Creating an adaptable platform based on the needs and preferences of the end user not only improves user satisfaction but also drives higher engagement and platform utility, ultimately making the platform more valuable to clients.

Last but not least, AI can help bolster operational efficiency in SaaS platforms. Integrating natural language processing guides, chatbots, and other instructional elements can help clients make the most of the platform without needing one-on-one interactions from the provider. Through AI, SaaS leaders can reduce the need for manual intervention, minimize errors, and speed up service delivery.

Even though AI is new and exciting, and it sometimes feels like businesses want to replace all of their current vendors with the latest AI tool they can get their hands on, clients don’t want to eliminate their investment in SaaS platforms. What they want is to know that the platforms they’re investing in are leveraging modern technologies like AI in the most effective ways possible. For SaaS providers, integrating AI helps bolster platform business cases and demonstrates to clients a willingness to adapt to the times.

[techavtar]

As a top technology service provider, Tech Avtar specializes in AI Product Development, ensuring excellence and affordability. Our agile methodologies guarantee quick turnaround times without compromising quality. Visit our website for more details or contact us at +91-92341-29799.

[reasonsforhope]

"Major technology companies signed a pact on Friday to voluntarily adopt "reasonable precautions" to prevent artificial intelligence (AI) tools from being used to disrupt democratic elections around the world.

Executives from Adobe, Amazon, Google, IBM, Meta, Microsoft, OpenAI, and TikTok gathered at the Munich Security Conference to announce a new framework for how they respond to AI-generated deepfakes that deliberately trick voters. 

Twelve other companies - including Elon Musk's X - are also signing on to the accord...

The accord is largely symbolic, but targets increasingly realistic AI-generated images, audio, and video "that deceptively fake or alter the appearance, voice, or actions of political candidates, election officials, and other key stakeholders in a democratic election, or that provide false information to voters about when, where, and how they can lawfully vote".

The companies aren't committing to ban or remove deepfakes. Instead, the accord outlines methods they will use to try to detect and label deceptive AI content when it is created or distributed on their platforms. 

It notes the companies will share best practices and provide "swift and proportionate responses" when that content starts to spread.

Lack of binding requirements

The vagueness of the commitments and lack of any binding requirements likely helped win over a diverse swath of companies, but disappointed advocates were looking for stronger assurances.

"The language isn't quite as strong as one might have expected," said Rachel Orey, senior associate director of the Elections Project at the Bipartisan Policy Center. 

"I think we should give credit where credit is due, and acknowledge that the companies do have a vested interest in their tools not being used to undermine free and fair elections. That said, it is voluntary, and we'll be keeping an eye on whether they follow through." ...

Several political leaders from Europe and the US also joined Friday’s announcement. European Commission Vice President Vera Jourova said while such an agreement can’t be comprehensive, "it contains very impactful and positive elements".  ...

[The Accord and Where We're At]

The accord calls on platforms to "pay attention to context and in particular to safeguarding educational, documentary, artistic, satirical, and political expression".

It said the companies will focus on transparency to users about their policies and work to educate the public about how they can avoid falling for AI fakes.

Most companies have previously said they’re putting safeguards on their own generative AI tools that can manipulate images and sound, while also working to identify and label AI-generated content so that social media users know if what they’re seeing is real. But most of those proposed solutions haven't yet rolled out and the companies have faced pressure to do more.

That pressure is heightened in the US, where Congress has yet to pass laws regulating AI in politics, leaving companies to largely govern themselves.

The Federal Communications Commission recently confirmed AI-generated audio clips in robocalls are against the law [in the US], but that doesn't cover audio deepfakes when they circulate on social media or in campaign advertisements.

Many social media companies already have policies in place to deter deceptive posts about electoral processes - AI-generated or not... 

[Signatories Include]

In addition to the companies that helped broker Friday's agreement, other signatories include chatbot developers Anthropic and Inflection AI; voice-clone startup ElevenLabs; chip designer Arm Holdings; security companies McAfee and TrendMicro; and Stability AI, known for making the image-generator Stable Diffusion.

Notably absent is another popular AI image-generator, Midjourney. The San Francisco-based startup didn't immediately respond to a request for comment on Friday.

The inclusion of X - not mentioned in an earlier announcement about the pending accord - was one of the surprises of Friday's agreement."

-via EuroNews, February 17, 2024

--

Note: No idea whether this will actually do much of anything (would love to hear from people with experience in this area on significant this is), but I'll definitely take it. Some of these companies may even mean it! (X/Twitter almost definitely doesn't, though).

Still, like I said, I'll take it. Any significant move toward tech companies self-regulating AI is a good sign, as far as I'm concerned, especially a large-scale and international effort. Even if it's a "mostly symbolic" accord, the scale and prominence of this accord is encouraging, and it sets a precedent for further regulation to build on.

[creative-anchorage]

Meta AI will respond to a post in a group if someone explicitly tags it or if someone “asks a question in a post and no one responds within an hour.” [...] Meta AI has also been integrated into search features on Facebook and Instagram, and users cannot turn it off. As a researcher who studies both online communities and AI ethics, I find the idea of uninvited chatbots answering questions in Facebook groups to be dystopian for a number of reasons, starting with the fact that online communities are for people. ... [The] “real people” aspect of online communities continues to be critical today. Imagine why you might pose a question to a Facebook group rather than a search engine: because you want an answer from someone with real, lived experience or you want the human response that your question might elicit – sympathy, outrage, commiseration – or both. Decades of research suggests that the human component of online communities is what makes them so valuable for both information-seeking and social support. For example, fathers who might otherwise feel uncomfortable asking for parenting advice have found a haven in private online spaces just for dads. LGBTQ+ youth often join online communities to safely find critical resources while reducing feelings of isolation. Mental health support forums provide young people with belonging and validation in addition to advice and social support. In addition to similar findings in my own lab related to LGBTQ+ participants in online communities, as well as Black Twitter, two more recent studies, not yet peer-reviewed, have emphasized the importance of the human aspects of information-seeking in online communities. One, led by PhD student Blakeley Payne, focuses on fat people’s experiences online. Many of our participants found a lifeline in access to an audience and community with similar experiences as they sought and shared information about topics such as navigating hostile healthcare systems, finding clothing and dealing with cultural biases and stereotypes. Another, led by Ph.D student Faye Kollig, found that people who share content online about their chronic illnesses are motivated by the sense of community that comes with shared experiences, as well as the humanizing aspects of connecting with others to both seek and provide support and information. ... This isn’t to suggest that chatbots aren’t useful for anything – they may even be quite useful in some online communities, in some contexts. The problem is that in the midst of the current generative AI rush, there is a tendency to think that chatbots can and should do everything. ... Responsible AI development and deployment means not only auditing for issues such as bias and misinformation, but also taking the time to understand in which contexts AI is appropriate and desirable for the humans who will be interacting with them. Right now, many companies are wielding generative AI as a hammer, and as a result, everything looks like a nail. Many contexts, such as online support communities, are best left to humans.