Hello Hussein, can you share with us your professional journey and how you became involved in the field of AI and technology, leading to your role as co-founder of Momentable?

I’ve always been fascinated with technology and sci-fi. AI is one of those things that sticks in your mind, and you can’t help but think about it.

I studied engineering and worked in tech, and even with all the advancements in technology we have been witnessing in the past two decades, AI was one of those things that we always thought would remain a sci-fi pipe dream for a long time.

This is not because there was nothing happening. But those who work in tech know it takes a while for the evolution of these technologies, and advancements are usually several degrees of separation from the regular user.

I’m always learning, reading, and building tech products, so AI was a field of study; however, implementing it was never accessible for early-stage products.

The status of AI has forever changed. OpenAI’s ChatGPT launch has had a remarkable impact on the field of AI and tech in general. AI is now available for regular users. People like me working in tech can now use AI in everything they are doing, which will accelerate product development and will impact the kind of products we can build and deliver to customers.

In addressing concerns surrounding AI ethics, you mentioned the importance of regulatory measures, technological transparency, and societal readiness. Could you elaborate on how Momentable approaches these areas to mitigate potential ethical dilemmas?

With great power comes great responsibility. AI is a powerful technology, and it’s very easy for those wielding it to amplify the impact of the good and the bad in the work they do.

While we, in the tech space, are doing our very best to build great products that deliver great value, we are not social scientists, psychologists, or public servants. So, we can’t be expected to regulate and supervise ourselves, nor can we evaluate the impact of these technologies and the products using them on the individual and on society.

It’s great when companies have values, codes of ethics, missions, and visions; however, those are not enough. Just like we do not rely on drivers to drive safely, we have traffic laws, signs, lights, and we make sure people driving a car are licensed and trained. We need to do the same with technologies, which, I would argue, have a massive impact on shaping our future as a species more than anything we’ve ever had in our history.

At Momentable, we are acutely aware of the impact of generative AI on our stakeholders, artists, cultural organizations, and art lovers. We engaged our stakeholders, ran several experiments where generative AI created artworks with input from artists, with their permission and consent.

In addition to using AI to enhance customer experience on our platform, we are using the learnings to evolve our product and introduce Generative AI in a thoughtful way that adds value and advances the art and culture space.

To Know More, Read Full Interview @ https://ai-techpark.com/aitech-interview-with-hussein-hallak/ 

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Generative AI technology like ChatGPT has brought the world one step closer to the futuristic society envisioned by forward-thinking science fiction writers. But will this future be a utopian or dystopian one? Time will tell. In the meantime, businesses must understand and leverage AI’s burgeoning influence over the zeitgeist to build favorable public sentiment about their brand’s reputation. It has become a make-it-or-break-it moment for corporations in the battle against the spread of AI-led misinformation.  

AI Angst

Opinions run hot, cold, and everywhere in between when it comes to AI’s possibilities and ramifications. A recent survey by the Pew Research Center found that 52% of Americans are expressing greater concern rather than excitement regarding the increasing dependence on AI. This sentiment has risen by 14% since 2022. The current era represents a Cognitive Industrial Revolution teeming with potential, including AI’s provocative ability to sway public opinion.

Businesses and their communication teams must fortify their message with an if-you-can’t-beat-them, join-them approach, leveraging AI’s influence over public opinion and using that to their advantage. By being open and transparent, companies can direct the narrative and strengthen their brand’s image by becoming thought leaders in their industry—with more communication, not less.

Better Communication Through Thought Leadership

Businesses are urged to become thought leaders, effectively communicating their brand message through credible third-party channels such as the media and influencers. The influencer marketing sector is booming and is expected to reach a value of $24 billion by year-end. AI is being embraced by 63% of companies for campaign executions, with 55% utilizing it to pinpoint influencers. Moreover, 33% of the total market capitalization of the S&P 500, attributed to goodwill, is impacted by public relations (PR) strategies and tactics.  Brands must proactively shape and manage their narratives to influence their target audiences. Failure to do so relinquishes control of these narratives to others—rendering marketing, and sales, less effective.

However, implementing this shift necessitates moving away from stale approaches in public relations and public perception. Traditional methods in these areas have been neglected, with only a minority understanding the strategic guiding of public opinion. As AI-generated content becomes more prevalent, the importance of compelling storytelling at the beginning of the customer journey or at the start or top of the PR>Marketing>Sales funnel cannot be overstated.

Mastering the Codified Body of Knowledge of Public Opinion

Companies benefit from becoming better acquainted with the established principles and empirical data that mold public perception. Delving into case studies, contemporary theories, rules of engagement, and the evolution of public relations offers valuable insights into the intricate dynamics that shape public opinion. Armed with this knowledge, organizations can develop strategies, and tailor messages that strike a chord with audiences, enhancing the prospects of broader acceptance and dissemination.

To Know More, Read Full Article @ https://ai-techpark.com/opportunities-in-the-cognitive-revolution/ 

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Another day, another AI headline. Meta has introduced new AI chatbots, embodied by celebrities, in a bid to mix information with entertainment. Amazon has invested up to $4B in its rival, Anthropic; and Google has launched Gemini, to compete with GPT-4. That’s just some of the AI stories within the last quarter involving three of the most influential companies in the technology sector.

Artificial Intelligence is booming. Its rapid development in 2023 has unlocked a wave of new possibilities and opportunities for the AI and machine learning ecosystem. But one of its beneficiaries isn’t. While AI stock has never been higher, we’ve not seen this optimism translate into the autonomous vehicle (AV) sector. This makes little sense. The development of AI and the future of autonomous vehicles is inextricably linked – the former quite literally powers the latter. So why is there this disparity in market confidence between the two sectors? And what does the surge in artificial intelligence mean for the AV sector as a whole?

The field of autonomous vehicles (AVs) has captured our imagination for decades. While self-driving cars are still a work in progress, the recent boom in artificial intelligence (AI) has the potential to be a game-changer. Let's explore how advancements in AI could transform the landscape of autonomous vehicles.

One of the most significant impacts of AI will be on the decision-making capabilities of AVs. AI algorithms, trained on vast amounts of driving data, can potentially react to complex situations faster and more consistently than human drivers.

The AV crystal ball

The challenges of AV at present are those of AI’s future. One of these big challenges revolves around data. An advanced driver assistance system (ADAS) or autonomous driving (AD) system relies on sensors (such as cameras and radar) to ‘see’ the world around them. The data these sensors collect is processed by machine learning to train an AI algorithm, which then makes decisions to control the car. However, handling, curating, annotating and refining the vast amounts of data needed to train and apply these algorithms is immensely difficult. As such, autonomous vehicles are currently pretty limited in their use cases.

AI developers outside the AV world are similarly drowning in data and how they collate and curate data sets for training is equally crucial. The issue of encoded bias resulting from skewed, low quality data is a big problem across sectors: bias against minorities has been found in hiring and loans, where in 2019 Apple’s credit card was investigated over claims its algorithm offered different credit limits for men and women. As applications of AI only continue to increase and reshape the world around us, it’s critical that the data feeding algorithms are correctly tagged and managed.

In other sectors, errors are more readily tolerated, even while bias harms. Consumers may not mind the odd mistake here and there when they enlist the help of ChatGPT, and even find these lapses amusing, but this leniency won’t last long. As reliance on new AI tools increases, and concern over its power grows, ensuring applications meet consumer expectations will be increasingly important. The pressure to close the gap between promise and performance is getting bigger as AI moves from science fiction to reality.

To Know More, Read Full Article @ https://ai-techpark.com/how-will-the-ai-boom-affect-autonomous-vehicles/ 

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In the rapidly evolving landscape of artificial intelligence (AI), media companies and other businesses alike continue to find themselves entangled in a web of lawsuits and public criticism, shining a spotlight on the issue of ethical transparency. Journalism has long been plagued by issues around deception — consumers often wonder what’s sensationalism and what’s not. However, with the latest casualty in the ongoing Sports Illustrated debacle, whose reputation greatly suffered after being accused of employing non-existent authors for AI-generated articles, a new fear among consumers was unlocked. Can consumers trust even the most renowned organizations to leverage AI effectively?

To further illustrate AI’s negative implications, early last year Gannett faced similar scrutiny when its AI experiment took an unexpected turn. Previously, the newspaper chain used AI  to write high school sports dispatches, however, the technology proved to be more harmful than helpful after it made several major mistakes in articles. The newspaper laid off part of its workforce, which was likely in hopes AI could replace human workers.

Meaningful Change Starts at The Top

It’s clear the future of AI will face a negative outlook without meaningful change. This change begins at the corporate level where organizations play a key role in shaping ethical practices around AI usage and trickles down to the employees who leverage it. As with most facets of business, change begins at the top of the organization.

In the case of AI, companies must not only prioritize the responsible integration of AI but also foster a culture that values ethical considerations (AI and any other endeavor), accountability, and transparency. By committing to these principles, leadership, and C-level executives set the tone for a transformative shift that acknowledges both the positive and negative impact of AI technologies.

To avoid any potential mishaps, workforce training should be set in place and revisited at a regular cadence to empower employees with the knowledge and skills necessary to combat the ethical complexities of AI.

However, change doesn’t stop at leadership; it also relates to the employees who use AI tools. Employees should be equipped with the knowledge and skills necessary to navigate ethical considerations. This includes understanding the limitations and biases as well as learning from the mistakes of others who’ve experienced negative implications using AI technologies, such as the organizations previously aforementioned.

To Know More, Read Full Article @ https://ai-techpark.com/how-to-reconcile-lawsuits-and-public-backlash/

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Artificial Intelligence (AI) has been developing at a rapid pace and has been integrated into a growing number of applications across every industry. AI continues to widen its capabilities to assist in a variety of daily tasks but, as can be expected with any Internet-based technology, AI also has a dark side. As cyberattacks have grown in volume and complexity over the last few years due to Covid-19, what could cybersecurity and AI look like going forward? If you want to know more about how Covid-19 affected cybersecurity, check out our blog “Cybersecurity in the post Covid-19 world.”

Preserving Privacy Around Artificial Intelligence

The cost of implementation for these types of integrated AI systems can be very high, making it an unattainable option for smaller businesses. Unfortunately, on the threat front, cybercriminals can use AI to devise and launch increasingly more complex cyber attacks. A study from 2023 by Blackberry stated that 51% of IT decision makers believe there will be a successful cyberattack credited to ChatGPT within the year.

Some malware architects have used AI to recreate malware strains and techniques described only in research publications, introducing an entirely new level of cyberattacks. For example, Chat GPT has successfully written functional malware that is capable of stealing sensitive files, encrypting hard drive content, and more. While this malware is not yet sophisticated, the speed and scale at which it can be produced is alarming. Additionally, other AI models have the capability to make attacks even more sophisticated by impersonating the voices of people and demanding money transfers. We can expect to see more attacks that are highly targeted social engineering attacks. Cybersecurity experts also state that AI-created deep fakes are finding ways to bypass biometric authentication, thus gaining access to protected systems.

We are still in the early stages of AI. These AI integrated systems need to be constantly monitored as they are far from perfect and can be prone to errors and biases. But it is clear AI products will continue to improve with time. When AI is used for corporate purposes, it is important that businesses which incorporate these AI systems ensure the technology is used for ethical purposes. These AI systems must be monitored to prevent them from being engineered to act against the corporate assets, and are not used to invade user privacy or circumvent traditional security measures – the  double-edged sword when it comes to security. While AI can provide benefits in threat detection and response capabilities, it can also pose a significant threat – be sure that your data is protected.

Simplify your data security needs. Encryptionizer is easy to deploy. It is a cost-effective way to proactively and transparently protect your sensitive data that allows you to quickly and confidently meet your security requirements. With budget considerations in mind, we have designed an affordable data security platform that protects, manages, and defends your data, while responding to the ever changing compliance requirements.
To Know More, Read Full Article @ https://ai-techpark.com/impact-of-artificial-intelligence-on-cybersecurity/

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Chatbots, powered by artificial intelligence (AI), are fundamentally changing how businesses operate and enhancing productivity and efficiency. Chatbots are computer programs designed to simulate conversation with human users via text or voice. From simple FAQ bots to complex virtual agents, chatbots are automating business processes and transforming how companies interact with customers and employees. The industry is still at the nascent stage but holds great promise and potential for the future.

In this post, we’ll explore the key ways chatbots are improving business productivity and efficiency.

Driving Business Efficiency

As AI systems, chatbots continuously improve through machine learning. They utilize data from past interactions to deliver ever more accurate responses and perform tasks more efficiently over time. Natural language interfaces allow chatbots to understand context and intent, engage in complex dialogue, and complete tasks just as a human assistant would. Companies are leveraging the technology to come up with optimal marketing strategies with AI and chatbots.

From customer service agents to sales reps and administrative staff, chatbots are taking on roles humans performed in the past at lower cost and with higher consistency. They don’t need holidays, sick days, or coffee breaks.  For many routine, repetitive tasks, chatbots simply offer a more efficient alternative. Intelligent chatbots are providing tremendous ROI through increased productivity and cost savings. But there are still domains where chatbots can’t function properly. Human touch and help are required in the form of on-demand tech support for various things like cybersecurity, cloud, office printer setup, computers, and network help.

Transforming Customer Experience

Today’s customers expect ultra fast, personalized, and seamless experiences. Intelligent chatbots provide a superior level of convenience by serving customers anytime, anywhere at the pace they expect. With NLP and machine learning, chatbots analyze customer data and past interactions to make recommendations and tailor experiences to individual needs and preferences.

Chatbots are revolutionizing industries from e-commerce retail to banking and travel. They minimize wait times, reduce human errors, and allow staff to focus on higher value functions like complex problem solving and building customer relationships. By streamlining the customer journey, chatbots drive satisfaction, loyalty, and revenues.

From large enterprises to smaller businesses, chatbots are fundamentally changing how companies operate; enhancing productivity, efficiency, and the customer experience. By automating repetitive tasks and processes, chatbots enable staff to focus on more meaningful, revenue-driving work. With intelligent self-learning capabilities, chatbots will only expand their capabilities and business value over time. Its clear conversational AI is transforming engagement across industries, delivering tangible returns on investment, and driving competitive advantage.
To Know More, Read Full Article @ https://ai-techpark.com/impact-of-chatbots-on-business-productivity-and-efficiency/

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Artificial intelligence (AI) holds an essential role in reshaping various industries and driving progress, as it can process vast amounts of data and derive valuable insights, enabling IT professionals, researchers, scientists, and more in various industries to make smarter and more data-driven decisions. This reliance on making decisions and executing tedious tasks can be eased with generative artificial intelligence (Generative AI or Gen AI), as it helps generate innovative solutions and strategic foresight by interpreting data on a large scale.

In recent years, with the popularity of generative AI tools like ChatGPT, PyCharm, Midjourney, Speak AI, and many more, businesses have been able to generate new ideas, solutions, and content faster, which helps streamline operations and allows businesses to stay ahead of a competitive and ever-evolving market.

This article delves into how generative AI works, the popular applications, and the use cases across industries.

How Does Generative AI Work?

Generative AI models use neural networks to identify patterns and structures with the help of existing data in the form of audio, text, or visuals to generate new and original content for their users. For instance, a popular application like GPT-3 allows users to generate essays based on short text requests.

With this data, generative AI can then step beyond just generating imitative content and also create a realm for multi-tasing and even create foundation models with the help of unsupervised or semi-supervised learning for training. For example, one stable diffusion, which is used as a base for AI systems to perform multiple tasks, allows users to understand the power of language.

Best Generative AI Applications

Generative AI is a powerful tool that helps streamline workflows for users from different industries. With the help of genetic AI models, one can take inputs like text, visual, audio, and code to generate new or modified solutions.

In conclusion, generative AI transcends the realm of mere artistic exploration, presenting itself as a powerful tool across various industries. Generative AI has not only emerged as a tool but as a collaborator for IT professionals, scientists, researchers, engineers, and many more to create ideas, solutions, and content of different forms through audio, visual, text, language, and coding; this will optimize workflow and spark a creative breakthrough. IT visionaries believe that generative AI offers a bridge between technical expertise and limitless possibilities.
To Know More, Read Full Article @ https://ai-techpark.com/generative-ai-applications-and-services/
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The inherent inertia and inefficiency of regulators in responding to rapidly evolving sectors like AI can be attributed to several factors rooted in their nature, design, and skill sets. First, regulatory bodies are typically structured to be cautious and deliberative, prioritizing stability and risk aversion over rapid adaptation. This approach, while beneficial for maintaining systemic integrity in traditional markets, often results in a lag when faced with fast-paced technological innovations. Additionally, the design of these institutions, often bureaucratic and bound by complex legislative processes, hampers their ability to swiftly enact new policies or adapt existing ones to novel contexts. Lastly, there is often a skill and knowledge gap; regulators may lack the specialized expertise required to understand and effectively govern cutting-edge technologies, leading to a reliance on outdated frameworks or overly cautious approaches that fail to address the unique challenges and opportunities presented by sectors like cryptocurrency.

This pattern of slow and inadequate responses was most recently highlighted by the rise and fall of FTX, a major cryptocurrency exchange. In 2021, FTX quickly grew into one of the world’s largest cryptocurrency exchanges. In 2022 it collapsed in one of the most prolific financial fraud cases in US history. This failure served as a wake-up call. It demonstrated the risks inherent in the crypto market and the consequences of the US government’s slow response in establishing a comprehensive regulatory framework.

Consumers are getting screwed

All these regulations will create negative consequences for consumers if not carefully crafted or if they “inadvertently” favor large companies at the expense of smaller ones or innovation in general. Primarily, a reduction in innovation and diversity, slower access to advanced technologies, and decreased competition are a few of many concerns. The best example of this happening is in Canada. The telecom industry consists of only three players: Rogers Communications Inc., Telus Corporation, and Bell Canada. This became possible as they lobbied and bullied their way into the top to introduce regulations to stifle any competition in mobile phone and internet services.

As a result, Canadians have significantly worse coverage plans, both locally and globally, than Americans do. Mobile phone bills have skyrocketed to eye watering prices, and Canadians are often the last to get many interesting and innovative services. This extreme competition stifling has even resulted in fatal consequences. On July 8th, 2022, Rogers Communications experienced a service outage that knocked 25% of Canada offline. This resulted in many crucial services being knocked offline, including 911 services.

What do we do then?

AI must be decentralized. Period. Full stop. Allowing something as game changing and powerful to be centralized and to follow the bottom line of business corporations is akin to allowing the internet to be controlled by corporations. If this had happened, this would have resulted in a much less free and open internet than the one we have today. Consumers of the internet today have freedom of choice in where they shop from, how often they do it, and what they wish to pay, due to the many services allowed on the internet. If it had been regulated like Microsoft had attempted to do in 1995, it would be akin to shopping in a random strip mall in midwestern America.

To Know More, Read Full Article @ https://ai-techpark.com/rapid-advancement-of-ai/

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In today's fast-paced world, organisations are constantly seeking innovative solutions to save time and money while enhancing productivity. Enter ChatGPT, a powerful tool that has evolved beyond its initial novelty status to become an indispensable resource for businesses across industries. Its applications in HR are particularly noteworthy, revolutionising traditional processes and opening new possibilities for streamlined operations. 

We are excited to present our comprehensive guide, designed to equip organisations with the knowledge and strategies needed to effectively implement and leverage chat GPT in HR functions. From mastering effective prompts to boosting employee engagement and satisfaction, this guide will empower you to harness the full potential of chat GPT and achieve unparalleled success in your HR strategies. 

The Role of AI in HR

Artificial Intelligence (AI) is revolutionising the HR industry. AI tools like ChatGPT can automate repetitive tasks, streamline processes, and provide valuable insights, allowing HR professionals to focus on strategic tasks that require a human touch. AI can enhance various aspects of HR, including recruitment, onboarding, employee engagement, performance management, and training and development.

How HR Professionals Can Use ChatGPT

• Recruitment: Create compelling job advertisements, generate relevant keywords for job descriptions, and draft outreach emails to potential candidates.
• Employee Engagement: Generate employee surveys and sentiment analysis, helping HR professionals understand employee needs and improve engagement.
• Performance Management: Preparing performance reviews, providing a consistent and unbiased evaluation of employee performance.
• Training and Development: Develop personalised career development plans, providing employees with clear pathways for growth within the organisation.

The Importance of Specific Prompts:

Specificity is crucial when working with ChatGPT. Clear and detailed prompts enable the AI model to generate more accurate and relevant responses. Vague or broad prompts can lead to less precise outcomes that may not address the user's needs effectively. In the context of HR, where precision and relevance are paramount, specific prompts play a pivotal role in maximising the potential of ChatGPT.

Case Study: Broad vs. Specific Prompts in HR:

Let's consider an example. An HR professional wants to use ChatGPT to generate interview questions for a candidate.

A broad prompt might be: "Generate interview questions."

While ChatGPT will indeed produce interview questions in response to this prompt, they may not be relevant to the specific role or candidate. The questions could range from generic ("Tell me about yourself") to technical ("Explain the concept of polymorphism in object-oriented programming"), depending on the AI's interpretation of the prompt.

Now, let's consider a more specific prompt: "Generate interview questions for a candidate applying for a mid-level project management role in the IT industry, with a focus on Agile methodologies."

With this prompt, ChatGPT has a clear understanding of the context and can generate questions that are far more relevant and useful, such as "Can you describe a project where you successfully implemented Agile methodologies?" or "How do you handle project scope changes in the middle of a sprint?"

The power of ChatGPT lies in its ability to generate human-like text that is contextually relevant and accurate. However, the quality of the output is heavily dependent on the quality of the input. By providing specific, detailed prompts, users can guide ChatGPT to produce the most useful and relevant responses, particularly in specialised fields like HR.

Unlocking Efficiency and Effectiveness in HR:
The integration of AI tools like ChatGPT in HR processes is not just a trend; it's a significant shift in how HR operates. By automating repetitive tasks and providing valuable insights, ChatGPT allows HR professionals to focus on strategic tasks that require human touch, leading to more efficient and effective HR operations. As the case studies illustrate, early adopters of this technology are already reaping the benefits, and it's clear that the use of AI in HR will continue to grow in the coming years.

As AI continues to reshape the HR landscape, mastering the art of prompting becomes increasingly crucial. Specific prompts empower HR professionals to guide ChatGPT in generating contextually relevant and accurate responses, driving enhanced outcomes. The early adopters of AI in HR have already witnessed the benefits, and the future holds even greater possibilities. By embracing ChatGPT and its potential, HR professionals can revolutionise their processes, elevate their operations, and create a more impactful employee experience.

For more information on how to leverage ChatGPT for successful HR and Talent Acquisition, download your free guide now!

As the number of generative AI tools continues to proliferate, companies must determine the risks and rewards of using the technology as well as design a framework for implementation

When it comes to generative artificial intelligence (GAI), there is no going back. The genie is out of the bottle and companies must now grapple with a number of big questions. For example, what guardrails should be put in place for employees looking to take advantage of AI’s tremendous potential? Do the risks associated with the emerging technology outweigh the benefits? Is there a way for humans and machines to co-exist in a mutually beneficial relationship?

GAI is different from what many people think of when it comes to AI. Instead of the human-like robots that are often portrayed in movies and the media, generative AI is a form of machine learning that can produce content – including audio, code, images, text, simulations, and videos – more quickly than humans can on their own. Which makes their use enticing.

Guidance principles for corporate use of AI

Implementing appropriate guidelines allows companies to use the power of generative AI while reducing the risk of being affected by its negative aspects. While no set standard will work for all companies, guidelines should adhere to three principles.

Principle 1: Be AI-safe and secure

When you submit a question to tools like ChatGPT, Google Bard, and Claude AI, that information is stored and used to train it further. Once businesses send information to these tools, they effectively hand over that data to an external entity and lose control over its use. And that has consequences.

“If you’re in healthcare, finance, or any other regulated environment, there are severe implications for misuse of the information you’re in charge of,” says Post. “Those types of organizations should not jump in until they have been properly trained and have guardrails put in place.”

LLMs can also open the door to intellectual property theft because people unwittingly give them proprietary information such as trade secrets, company financial data, personally identifiable information from clients, and customers, and much more.

Safety, security, and privacy comprise the first guiding principle and ensure employees do not input anything into a generative AI tool that they should not share.

A collaboration between bytes and brain

The guidance principles are meant to raise awareness about the current state of AI tools. Humans will need to learn to work with AI, not rebel against it.

“It’s a bytes and brains collaboration,” says Dr. Norrie. “We must figure out the machine instead of letting the machine figure us out. It is best to establish your AI guidelines while you’re developing your own knowledge and understanding of how you plan to govern and regulate its use.”

To Know More, Read Full Article @ https://ai-techpark.com/navigating-the-future-of-generative-ai/ 

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