Author: Franz Malten Buemann

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Responsible AI — deployment framework

I asked ChatGPT and Bard to share their thoughts on what policies governments have to put in place to ensure responsible AI implementations in their countries.

Bard:

Here are some policies that governments can put in place for responsible AI use:

• Ethical guidelines: These guidelines should outline the principles that AI systems should adhere to, such as fairness, transparency, and accountability.
• Regulations: These regulations should set out specific requirements for the development, deployment, and use of AI systems. For example, they could require companies to conduct impact assessments before deploying AI systems or to provide users with information about how AI systems work.
• Education and awareness: Governments should invest in educating the public about AI, including its potential benefits and risks. They should also work to raise awareness of the importance of responsible AI among businesses and organizations.
• Funding for research: Governments should invest in research on responsible AI, such as research on how to develop AI systems that are fair and unbiased.
• International cooperation: Governments should work together to develop and implement responsible AI policies. This could include sharing best practices, coordinating research, and developing common standards.

It is important to note that there is no single solution to the challenge of responsible AI. Governments will need to take a multi-pronged approach, and they will need to continue to work to develop and refine their policies as AI technology evolves.

ChatGPT4:

Governments can implement various policies and regulations to encourage responsible AI use. These policies aim to ensure that AI systems are ethical, transparent, and accountable and provide social benefits while mitigating risks. Some potential policies include:

1. Establishing AI ethics guidelines: Governments can create a set of ethical principles to guide AI development and deployment, addressing issues such as fairness, transparency, accountability, and human rights.
2. Enacting data protection and privacy regulations: Governments can implement regulations that protect individuals’ data and privacy, including requiring organizations to obtain consent for data collection and use and ensuring data anonymization.
3. Ensuring algorithmic transparency: Governments can mandate that AI systems be transparent in terms of their functioning, decision-making processes, and data sources. This may involve requiring organizations to provide explainability for AI decisions.
4. Creating accountability frameworks: Governments can establish legal and regulatory frameworks that hold AI developers and users accountable for the consequences of their AI systems, including potential biases, discrimination, and errors.
5. Investing in AI education and public awareness: Governments can support education initiatives that teach people about AI, its benefits, and potential risks and promote public understanding of AI ethics and responsible use.
6. Encouraging AI audits and certification: Governments can create independent bodies to audit AI systems and certify their compliance with ethical guidelines and other regulatory requirements.
7. Ensuring fairness and inclusiveness: Governments can implement policies to prevent discriminatory outcomes and ensure that AI systems are developed and used in ways that benefit all members of society, including underrepresented and marginalized communities.
8. Promoting international cooperation: Governments can collaborate with other countries to establish global AI standards and guidelines, share best practices, and address cross-border issues such as data governance and AI safety.
9. Investing in AI safety research: Governments can fund research and development efforts focused on AI safety, long-term risks, and the prevention of unintended consequences.
10. Supporting AI for social good: Governments can encourage the development and deployment of AI applications that address societal challenges, such as healthcare, education, and environmental protection, and provide incentives for organizations working on these projects.

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Responsible AI — deployment framework was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Did you know that the global chatbot marketing revenue has reached $83.4 million this year? This stat clearly states how popular and reliable chatbots have become for businesses. And this is why many marketing agencies are looking to include chatbots in their suite of offerings. If you are also such a marketing agency, you should not miss out on becoming a white label chatbot reseller.

Being a chatbot reseller, you can purchase a bot builder platform from a company, put your logo & branding, and can resell it to your clients at your price. In addition, you can also accommodate customized chatbot requests with the help of your white label chatbot partner.

Many people have misconceptions about chatbots. They think since chatbots are so much in demand, it will require a huge amount of investment to become a chatbot reseller. But that’s not true, You can become a chatbot reseller with no to little investment and risks.

Along with this, you can benefits like:

• Higher customer satisfaction among clients
• Lucrative addition to your current suite of offerings

This is just the tip of the iceberg. There are many more reasons why you should consider becoming a chatbot reseller.

Let’s explore them.

1. High Demand

As I mentioned earlier, chatbots are in high demand, and their popularity is rising every day. This is because chatbots serve numerous benefits:

• Lead generation
• Customer engagement
• Automation
• Self-service
• Customer support

Plus, the constant updates and evolution of chatbots are bringing new features and functionalities for their users. These features help the clients to serve best to the end customers.

Because of all these reasons, people are investing in enterprise chatbots. And being a white-label reseller, you can earn profits as high as the demands of chatbots.

With time, businesses want more automation and less dependency.

Here, chatbots are a perfect fit to let end customers enjoy self-service while it generates automatic leads for the businesses.

With fast and responsive AI-based chatbots, your clients’ can enhance their customer experience like no other tools. You will only require a white-label partner that provides you with a chatbot builder to make required chatbots for your clients and resell them.

2. Low Investment, High Returns

When I said earlier that you need a low investment for reselling chatbots, I truly meant it. You just have to invest your time and efforts to build a chatbot with the help of a ready and updated platform.

Once you explore its features and abilities, you will be able to understand its potential deeply and will be able to fetch more clients. You can decide a price as per project specifications and sell it to the clients.

Reselling it at your price will increase your revenue, and the white-label partner will take care of customer satisfaction. It is because the bot agency has years of experience and niche-wise expertise on board, so you don’t have to worry about the quality.

3. New Revenue Stream

Doing just the bare minimum will give you only the bare minimum returns.

To earn more returns, you need to stand apart from the crowd. As a reseller, you need to resell software that is high in demand but still has lower competitors.

Offering website development, ad management, and social media management is common, and the whole world is doing it already. This lowers your chances of getting a client, or you might have to decide the prices as per market prices to get clients.

But that’s not the case if you become a chatbot reseller. This stream is currently not explored as much as it is in demand. You can take advantage of this, build your client base, and resell chatbots at your price easily.

This will also make you stand apart from the crowd for serving unique services which are helpful to businesses in various areas. Adding a chatbot offering will make it easy for you to find clients, and the end benefit of it would be high revenue and excellent brand awareness.

4. Tried and Tested Solution

No matter what you do, you cannot run from risks; however, reducing them is an option. When you build a chatbot from scratch as per the client’s requirements, it will eat up a lot of time, effort, and cost.

While if you resell the chatbot that is made exactly as per clients’ requirements using a chatbot builder, then it will save you time and effort and will give you higher revenue.

One more thing to take into consideration is the testing time. When a chatbot is built, one needs to perform various tests to ensure it does not have any flaws. This process results in reworking or correcting codes and is usually a time-consuming process.

But as a reseller, you don’t have to worry about this phase as the white label partner would ensure that there are no flaws in the bot before selling it to you.

You just need to make them understand the client’s requirements, and that’s it. The bot agency will provide a tried and tested solution to which you can add your logo and sell it at your price without any hassle or worrying about the quality.

Final Words

With the evolution of this digital era, chatbots are going to rule the market just as social media did or is still doing. People who used social media for marketing as soon as they knew its potential got unexpectedly good results. Their brand awareness also increased rapidly.

They became new trendsetters and had a higher customer base in comparison to the ones still following billboard ad or traditional marketing strategies.

In the same way, reselling chatbots is still a new concept that can deliver promising results. You can grab it and rule the market with the highest customer base in the industry.

Bot agencies that are white-label chatbot sellers can provide you with everything your client needs in a chatbot, and you will only have to resell it at your price.

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4 Reasons to Become a Chatbot Reseller was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Chatbots and virtual assistants are quickly becoming an essential part of the customer experience. They can help businesses provide faster and more personalized service, increase customer satisfaction, and even generate revenue.

Don’t miss out on the chance to learn how to design and develop chatbots, and gain certification in Conversational AI Design, NLU, and ChatGPT at our upcoming Conversational AI workshop..

Best regards,

Stefan

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The Future of Customer Engagement 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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After 2010, SaaS-[Software as a Service] became a trend in the market. Just think from your sixth sense, OpenAI just launched ChatGPT, which made a buzz in the global market. That would have a major impact on IT companies globally. Now let’s take a scenario: if we integrate OpenAI with an existing SaaS product, what would the result be?

Actually, many companies in the USA are working towards AI-SaaS integration. They have started understanding the pros and cons of AI with their SaaS products, like…

• Many chatbots are getting automated using AI.
• Docker is one of the strong examples of AI-powered products.

So what are the Benefits of Integrating AI in SaaS?: The most important point is that SaaS with AI offers more quick software and web development than on-premises software. That directly reflects the revenue model of the company.

Also, there are many advantages of AI integration; let’s have a look:

1. Automation means getting rid of manual tasks.
2. SaaS + AI is also a good cost-saving option
3. Augments Efforts for Human Welfare
4. Detection of malware and black-hat activities on the site
5. Detection poor performing areas of the company
6. Helping almost each and every industries

Apart from that, there are some well-known SaaS platforms that are integrated with AI and performing well compared to earlier.

1. Crowdstrike: This is a cybersecurity platform that provides cloud workload and endpoint protection, threat intelligence, and cyber attack response services. After the integration of AI, the users may see if there are any malfunctions happening in their product, and organizations can take appropriate action against the same.
2. Domino Data Lab: Domino Data Labs provides a system of record that tracks all data science activity across an organization and acts as an orchestration layer on the AWS storage foundation. This is the perfect example of SaaS integration with AI. After integration, the users can compile information by testing various AI models and get better results for future forecasts.
3. Apptio: Apptio is USA based licensing, strategy, and capital expenditure SaaS development company. They also integrated AI into their platform to advise other companies on the best services for their resources.

Hunting for a SaaS development company?

Yes, there are tons of benefits to integrating AI with SaaS. Also, it is cost-effective and also provides secure solutions for your product. Apart from all this priceless information, I would recommend a SaaS development company that has 11 years of experience with 80+ dedicated SaaS developers. Have a look at how Bacancy is making businesses successful by integrating AI with SaaS.

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SaaS Development with OpenAI: A Perfect Combination was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

Best Practices for Outsourcing Development

Introduction

Chatbots have become an increasingly popular way for businesses to interact with their customers, providing quick and efficient customer service and support. However, building a chatbot requires specialized skills and expertise, which many businesses may not have in-house. As a result, outsourced chatbot development teams have become a common solution for businesses looking to build and deploy chatbots quickly and efficiently. In this blog, we will discuss best practices for managing outsourced chatbot development teams to ensure successful collaboration and project delivery.

Defining Roles and Responsibilities

Before starting any chatbot development project, it’s important to define the roles and responsibilities of each team member. This includes identifying the key roles in chatbot development, such as developers, designers, and project managers, and assigning specific tasks and deliverables to each team member. Clear expectations and deliverables should be set to avoid any confusion or misunderstandings.

Effective Communication

Effective communication is critical for successful collaboration with outsourced chatbot development teams. Establishing communication protocols, such as regular check-ins and progress reports, is important to keep everyone on the same page. Providing timely feedback and updates is also essential to ensure the project stays on track. Project management tools, such as Trello or Asana, can be used to facilitate communication and keep everyone informed.

Building Trust

Building trust with outsourced team members is important to establish a strong working relationship and ensure successful project delivery. Transparency and accountability are essential for building trust, so it’s important to share progress updates and be open to feedback. Offering incentives and recognition, such as bonuses or public recognition, can also help motivate team members and build trust.

Ensuring Quality

Ensuring quality is crucial for delivering a successful chatbot project. Establishing quality standards and metrics, conducting regular code reviews, and implementing automated testing are some best practices for ensuring quality. Regular quality checks should be performed throughout the project to catch any issues early on.

Addressing Cultural and Language Differences

When working with outsourced chatbot development teams, it’s important to be aware of any cultural and language differences that may impact the project. These differences can range from basic language barriers to more complex cultural differences that affect how people approach work and communication.

To address these differences, businesses should take a proactive approach to understand the cultural and language backgrounds of their outsourced team members. This can be done by conducting cultural awareness training, which can include information about cultural norms, communication styles, and work expectations.

In addition to training, businesses can also use translation and cultural adaptation tools to facilitate communication. Tools like Google Translate can be useful for translating written communication, while video conferencing and phone calls can help to bridge language barriers for verbal communication.

Finally, offering cultural training and education can also help to bridge cultural gaps and ensure successful collaboration. This can include training on cultural norms and expectations, as well as language classes to help team members improve their language skills.

Overall, addressing cultural and language differences is an important part of managing outsourced chatbot development teams. By taking a proactive approach to understanding and addressing these differences, businesses can improve communication and build stronger working relationships with their outsourced team members.

Conclusion

In conclusion, managing outsourced chatbot development teams requires clear communication, established roles and responsibilities, trust-building, quality assurance, and awareness of cultural and language differences. By implementing these best practices, businesses can successfully collaborate with outsourced teams and deliver high-quality chatbot projects. As chatbots continue to grow in popularity, outsourced chatbot development teams will continue to play an important role in helping businesses build and deploy chatbots quickly and efficiently.

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Best Practices for Outsourced Chatbot Development Team Management was originally published in Chatbots Life on Medium, where people are continuing the conversation by highlighting and responding to this story.

The commercial availability of ChatGPT and the subsequent developments have sparked off major debates in academia, the corporate world, and government on:

• Will AI affect white-collar or blue-collar jobs the most?
• How will it impact skill adjacencies?
• Will the tech lead to a major re-skilling of the workforce? Or will it require upskilling?
• (The most important question of them all). Will AI get rid of most jobs because of automation?
• What and how will the tech impact a nation’s overall productivity?

Skill adjacency is a generic though sophisticated term to describe the connections between an employee’s present-day skills and those they need to acquire based on emerging needs.

For example: If you are a professional photographer, is it time now for you to upskill and learn how to use image editing software?

A professional photographer may also choose to reskill by learning videography or even social media marketing to expand his/her offerings. Visual content is his/her forte, and upskilling or reskilling revolves around the core competency. Mostly. One of the duties of HR professionals the world over is to try and understand the linkages that can be leveraged to get workers to get to such upskilling and reskilling opportunities.

Which is all very fine, but the very nature of the technology that AI represents constantly re-routes all doubts and queries to this one destination — the fear uppermost in most employees’ minds — Will most jobs become automated?

On AI-induced job losses, if the views of the doomsday brigade were to be kept aside, the consensus among social scientists and AI experts, for now, is there will be a percentage of jobs that will disappear, but a percentage of this percentage will be replaced with new job profiles. So there’s some hope.

Here’s a thumb rule that many experts ask today’s workers to follow:

Ask yourself whether you currently do a repetitive job. Does it also involve data? If the answer is yes to both, there is a huge probability that your job will be taken over by AI.

Some experts have tried to drill deeper. Which kind of job profiles will become redundant or over-written by others? Also, will it be blue or white-collar jobs, predominantly?

Again, there are no clear answers, but increasingly the conversation is veering to this — highly skilled white-collar workers may be most affected than anybody else in the workforce. Office-based work like customer service, Sales and Marketing, and jobs that rely on cognitive expertise will be most impacted.

So Will AI Significantly Impact Only High-paying Jobs?

A 2019 research report by the American research group Brookings Institution (slightly before ChatGPT came online) has actually spelled out the jobs that could face the highest exposure to AI. The entire report’s forecast is that better-paid, better-educated workers face the most exposure because of AI. Workers with graduate or professional degrees will be almost four times as exposed to AI as workers with just a high school degree, it said.

The jobs listed below have the highest exposure, as per this report:

• Chemical engineers
• Political scientists
• Nuclear technicians
• Physicists
• Occupational therapists
• Gas plant operators
• Administrative law judges, adjudicators, and hearing officers

Reference: Brookings. edu

An even earlier report by McKenzie, however, claimed AI would impact blue-collared jobs like fast food service and machine operations the most.

A report by the World Economic Forum released on May 1, 2023, lists the fastest-growing and declining jobs:

There will be more studies in the future on the impact of AI on jobs, but for now, the haze is slowly lifting. So, even though the picture may not be very clear yet, the coming job displacement wave will, most likely than not, affect the highly skilled and the extremely poorly skilled workers.

Let’s say you are a radiologist interpreting medical scans of a suspected TB patient. As a human, you take at least a day or two to come up with a report. Which is also mostly based on your experience of having studied previous such scans, coupled with your formal education. An algorithm with the right training dataset, which means thousands of scans of other TB patients, will be able to do the job far better than a human. And, within minutes. And with a far greater degree of accuracy. Which will then mean the radiologist will now have to upskill.

Poorly skilled workers will be affected in a slightly different way. For this lot, AI will be the tool to help them learn and bring them to the level of their already well-trained counterparts.

In one interview, Stanford professor Erik Brynjolfsson reveals how AI can identify skill adjacencies to bridge the skills gap. In an article by the World Economic Forum, he extends the example of a forensic expert. If you were to take a forensic accountant and teach them some cyber, they can become a cybersecurity expert, maintains Erik.

Reference: Weforum.org

Microsoft Study Finds Employees Want To Forge Partnership with AI

Here’s something surprising. Despite concerns over job displacement, a study has shown that employees were more eager for AI to ease their workload than they were afraid of being replaced by it.

The study by Microsoft spoke to 31,000 people in 31 countries and analyzed trillions of Microsoft 365 productivity signals, along with labor trends from the LinkedIn Economic Graph.

The report said although 49% of workers feared that AI may take their jobs, 70% would prefer to delegate as much work as possible to AI to alleviate their burden.

Reference: Microsoft

Research paper author and organizational psychology professor Adam Grant called the finding “intriguing”. People are more enthusiastic about AI rescuing them from burnout than they are anxious about it eliminating their jobs, he pointed out.

The survey revealed that people are seeking AI assistance in almost every aspect of their work, with 3 out of 4 respondents indicating that they would be comfortable using AI for administrative tasks (76%), analytical work (79%), and even creative work (73%). Furthermore, people are also interested in AI’s help with finding information (86%), summarizing meetings (80%), and planning their schedules (77%).

Automation introduced by AI is a general apprehension uppermost on everybody’s minds, but the fear is taking attention away from another critical question — the re-engineering of society’s fabric and the role corporates will play in it.

Will Coming Shift in Job Profile Worsen Society’s Disparities or Correct Them?

Productivity growth is a crucial factor in a nation’s economic prosperity. Efficiency because of AI will increase, which almost everybody in the ecosystem seems to agree upon. For now. But will it be the same for productivity?

As shocking as it may sound — productivity growth has remained stagnant in the US and other advanced economies since around 2005, according to this report. This means workers’ wages have, by and large, remained in the same range between then and now.

This lack of growth has also worsened income and wealth inequality. Now, some experts fear that the coming re-jigging of employment and job profiles may widen the income gap.

Will AI break this impasse and raise productivity so much that even as it displaces a lot of jobs, it creates new ones and raises living standards? If yes, how will it tie into a nation’s overall productivity?

Since November 30, 2022, when ChatGPT was announced, and the competitors of OpenAI also jumped into the AI race, it’s becoming clear that this marathon, too, will be run by the ad-revenue motivated Big Tech such as Google and Microsoft. This means that the large language models will be dominated by the same big companies that have ruled much of the digital/internet world for decades.

The concern is that these companies may use this new, AI-led automation to replace comparatively well-compensated white-collar jobs, leading to a shift for these workers towards lower-paying service roles. Meanwhile, a small group of individuals who are most adept at utilizing the new technology may reap most of the benefits.

In a well-argued, well-presented article in MIT Technology Review, Editor David Rotham talks of the “gold rush” sparked off among companies because of generative AI. David says the focus is — how do we (corporates) make money out of this?

The upcoming revolution of large language models, represented by ChatGPT, he points out, is expected to bring significant changes to the economy. The question is how we will shape this transformation. The impact on various jobs is inevitable, and it is up to us to determine whether this change will result in widespread prosperity or not, writes David.

Initial findings, says the report, indicate that ChatGPT and other generative AI systems could potentially provide “upskilling” opportunities for those struggling to secure employment today. Current AI adoption in companies has been limited to optimizing tasks incrementally, leading to only marginal productivity and efficiency gains.

How much, how little? Productivity jump or mere enhancement? Redefinition of skills or their complete loss? Even more disparity or the comeback of some semblance of equality in society? These and many related questions continue to be probed, studied, and debated by our social scientists, economists, technology experts, and psychologists. For now, though, the consensus is only around very few hypotheses.

As for the answers to the remaining questions, subscribe to my newsletter — AI For Real — to keep track and be updated as AI evolves over the coming years.

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AI’s Impact: Examining the Effects on High-Paying and Low-Skilled Jobs 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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