It may be too early to tell ChatGPT’s specific effect on education, but teachers are already theorizing, especially since it’s still in the developmental stages. Controversies abound, as with any nascent technology. Here are the most prominent discussions in education today as ChatGPT grows in popularity and the industry faces change.

“Everyone is contributing to the bot’s growing conversational abilities, and teachers and students are inventing creative uses that could help and hurt schooling permanently.” 

Debating for a Ban

ChatGPT is already causing a stir in education. Schools worldwide advocate for the ban of the chatbot in schools and educational-related endeavors. The AI’s advanced employment of natural language processing and conversational comprehension makes it ripe for producing plagiarized content, helping students cheat, or spreading misinformation. Kids studying language have attempted to cheat using Google Translate for as long as it has been around, and there are similar concerns with ChatGPT.

ChatGPT is the most advanced AI of its kind, and its accessibility is the primary consideration. It’s easy to use, and educators and administrators must admit it’s challenging to tell when a typed response is AI-generated or not nowadays — especially when ChatGPT could write entire essays within minutes. The temptation for students seems too alluring, causing teachers to act with an all-or-nothing mentality to maintain the sanctity of education the best they can.

However, not everyone is on the same page. Whereas some educators feel it will encourage cheating and perpetuate distrust between teachers and students, others feel ChatGPT is an educational resource with untapped potential. Widespread societal AI integration is inevitable, so shouldn’t students learn to navigate learning alongside it? Dismissing phenomena like this entirely provides an unrealistic environment, especially for kids going into tech-reliant sectors that will undoubtedly employ AI.

Reconciling Paranoia

Will ChatGPT make assigning homework moot? Adversely, students could question if teachers are grading their work — why couldn’t ChatGPT? 

Questions like this bring another effect of ChatGPT to the surface, and that’s the changing mindset of educators. Teachers’ paranoia surrounding ChatGPT could develop toxic relationships between teachers and students. Educators who assume kids will utilize this tool to cheat feed the mentality that no child is trustworthy or values education. Instructors can act proactively instead, finding ways to overcome the adverse side effects of its capabilities for more positive outcomes.

These sweeping, unrealistic mindsets cannot permeate education. Otherwise, the system will become complacent and fatalistic rather than embrace the potential of technology. It also eliminates the nuance of learning. ChatGPT could help write essays, but it’s a leap to say it could replace every facet of literary education. It doesn’t train students to empathize with the reading audience or how to feel inspired.

“Teachers’ paranoia surrounding ChatGPT could develop toxic relationships between teachers and students.” 

Ultimately, ChatGPT affects education by making students and teachers question the value of their efforts. So long as humanity inherently values learning, there will always be a need for traditional education alongside evolving tech, regardless of ChatGPT’s potential. Plus, it could help students and teachers equally.

Teaching With ChatGPT

History proves that banning tempting products never ends well and leads to more rebellious behavior. Keeping students from using the tool in school buildings doesn’t prevent home usage or the desire to use it in the first place. Therefore, a ban probably isn’t the answer for those in the opposition. Instead, educators should find helpful ways to show the tool’s capabilities that spur creativity and critical thinking.

Teachers could try experimenting with the tool themselves to see how they could innovate lesson plans using ChatGPT. Instructors bored with their decades-old lessons can look to ChatGPT to modernize. AI could also help teachers navigate complex individualized education plans (IEPs) that promote competency-based education for nontraditional learners, such as students with disabilities.

“Educators should find helpful ways to show the tool’s capabilities that spur creativity and critical thinking.” 

An Oregon high school teacher made students use ChatGPT to create outlines for English essays for literary analysis. Then the students wrote them manually. The variances made each response unique and challenged kids to perceive the stories in innovative ways. Students who created their own outlines had fewer original ideas or opportunities to test their reading skills as they attempted to make connections and find evidence.

Teachers can also encourage students to use ChatGPT as a tutoring resource. Kids could ask it for definitions or to re-explain complex concepts as they do their homework. These are examples of how instructors could instill moral values in students by interacting with technology to benefit their education instead of using it to cheat.

AI’s Entrance to Education

Students are using ChatGPT to cheat and teachers are finding ways to use it to make lesson plans. The versatility of this tool is unmatched, yet educational systems must adapt to sustain healthy relationships with technology and learners. 

Engagement with these complex, ethical ideas will create a more nourishing educational environment and prepare teachers for the inevitable adverse repercussions. At least there will have been considerable thought on navigating these technological waters as conversational AI becomes the norm.

Also, Read Using Generative AI for Educational Purposes

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The world produces roughly 400 million tons of plastic waste annually yet recycles less than 10%. Tackling this issue will require substantial, complex changes, but AI can provide the insight and efficiency necessary to address it.

Finding Ways to Reduce Plastic Consumption

The first way that AI can reduce plastic waste is by lessening how much of this material we use in the first place. Some companies have started using AI to analyze and simulate various packaging designs to see how they could redesign them to provide the same strength with less material. Businesses that make these changes consume less plastic.

Similarly, AI can simulate how alternative materials could replace plastics in products and their packaging. Businesses can use this insight to switch to more sustainable, easily recyclable materials without long, expensive prototyping processes. Finding ideal adjustments by manual means could take months and involve multiple costly missteps, but AI can do it quickly and effectively.

“AI can simulate how alternative materials could replace plastics in products and their packaging. ” 

Optimizing Plastic Supply Chains

AI can also improve supply chain operations to make them less wasteful. Predictive analytics can give a better picture of demand shifts, helping companies avoid overproduction. By tailoring production to changing demand cycles, AI can help businesses only use as much plastic as they need, generating less waste.

Some organizations aim to create a closed-loop supply chain, which involves recycling and returns to remove waste from production. Figuring out how to develop and implement these systems involves complex considerations, but AI can help. 

Analytics engines can determine where companies can reuse materials or how best to run the returns process. That will make it easier for businesses to reorganize their supply chains to eliminate plastic waste.

Discovering New Disposal Methods

Alternatively, AI can find novel, environmentally friendly ways to dispose of plastics. Scientists recently used machine learning to create an enzyme that takes less than 24 hours to break PET plastics into their chemical components. Companies can form these components into new materials, preventing waste.

Traditional discovery methods are slow and resource-intensive, often involving several lab experiments. Machine learning algorithms can streamline the process by simulating how various chemicals interact. They can then reveal promising candidates far faster and more accurately than conventional research.

Similar AI-assisted research could reveal more ways to break down plastics. These discoveries could be crucial in preventing future waste and in handling current plastic pollution.

“Scientists recently used machine learning to create an enzyme that takes less than 24 hours to break PET plastics into their chemical components.” 

Reducing Wasteful Errors

AI can help improve more traditional disposal methods, too. Recycling centres often rely on manual sorting processes to remove recyclable plastic from landfill-bound waste. Since repetitive work like this is often difficult or tedious for humans, mistakes are inevitable, but AI can change that.

Machine vision systems can distinguish between recyclables and waste faster and more accurately than humans. Importantly, they’ll also reach the same speed and accuracy at any moment, unlike people, who get bored and distracted. Recycling centres can then prevent mistakes that would send recyclable plastic to landfills.

Similarly, machine vision and other AI applications in production facilities can prevent errors in manufacturing. These tools will reduce material waste by making plastic production less error-prone.

Guiding Pollution Removal Efforts

In addition to reducing future waste, AI can address past mistakes. There are currently 50-75 trillion pieces of plastic floating in the world’s oceans, and removing this waste from the environment is crucial to protecting marine life. Doing so manually is inefficient and expensive, but AI can automate the process.

Machine vision can help swimming robots recognize plastic waste to collect and bring it to recycling centres. As these robotic systems work, they’ll also gather data about where plastic ends up and where it comes from. Analytics algorithms can then assess this information to inform policies and business decisions to prevent similar waste in the future.

Some companies also use machine vision-powered drones to fly over oceans and determine where the most waste is. These readings can guide more effective cleanup efforts, helping environmental organizations make the most of their time and resources.

“Machine vision can help swimming robots recognize plastic waste to collect and bring it to recycling centers. ” 

AI Can Help Fight Plastic Waste on All Fronts

The plastic waste problem may be daunting, but AI is a powerful ally in the fight for the environment. This technology can improve processes and provide insight across every part of the production, use and disposal cycle, reducing and eventually eliminating waste.

Eliminating plastic waste will take considerable time and effort, but AI is making it quicker and easier. The world will become a cleaner place as more organizations implement this technology.

Also, Read Why Logistics Industry Should Embrace AI

The post Leveraging Artificial intelligence (AI) To Reduce Plastic Waste appeared first on AiiotTalk - Artificial Intelligence | Robotics | Technology.

If you’re an eCommerce store owner, you need to know why machine learning is growing in popularity.

When integrated into marketing and other strategies and operations, machine learning offers many game-changing advantages with its powerful capabilities.

As a result, you can significantly increase your conversions and sales, augment your efficiency, improve customer engagement, and much more.

That makes machine learning and their capabilities worth studying. Doing so helps you apply its concepts dynamically in your business.

If you haven’t found substantial reasons on why you should learn machine learning, allow me to share four reasons to learn machine learning.

Let’s dive in.

1. Machine Learning Enhances item Searches.

Machine learning improves customer shopping experience through relevant and precise item searches.

Here are two examples:

a.  Intuitive Word Query

When you enter a “red dress shirt under $20” on an eCommerce store, you expect to see results resembling a 20-dollar red dress shirt, right?

You’d probably say, “yes.”

However, if the results showed black dresses or 30-dollar red t-shirts, you’d probably feel dismayed.

You’d wish the search mechanism thought as humans do, so it can give you precisely what you’re looking for.

Thankfully, machine learning can understand you.

Use tools like Twiggle. 

Image Source: Twiggle

Through machine learning and natural language understanding, Twiggle makes direct connections between your customers’ search and your product information. 

It can comprehend keywords you usually use to describe an item, like product type, color, price, material, and more.

Even when you don’t mention the keywords, Twiggle still has a clear grasp of your search. It can understand dimensions, synonyms, use cases, and other linguistic aspects.

Twiggle, with its machine learning capabilities, continues to self-learn and evolve as our human linguistic phenomena also change.

Such an unsupervised learning capacity of machine learning is not only powerful but also beneficial as you serve more customers and obtain more data.

If you study machine learning, you can also uncover how to make relevant, customer-centric searches like Twiggle did, and more.

To study that field, you can enroll in a machine learning online certification training course. 

In that course, you will learn concepts and practical applications, such as forecasting fare and customer privileges.

Mastering these skills may take time and effort, but if you persevere, you may even build tools like Twiggle suited for your business.

b. Visual Search 

Visual search allows you to find an item with images if you’re having a hard time searching through keywords. 

Take a look at a tool called Syte:

                                                                                                                                    Image Source: Syte

With Syte, you can find similar items from the e-commerce store by taking a photo or uploading one.

Through machine learning, along with image detection, Syte recognizes attributes like color, size, similarity, etc. 

It can even recommend similar products or ways to wear the item, and your customers can purchase right after the search.

Visual search helps your customers find and buy desired items with less hassle and delay, thus increasing your sales and conversions.

2. Machine Learning offers Customer Support Online.

As a business owner, you recognize that customer support is a crucial aspect of your business. However, you may be limited to attending to queries in real-time when you’re offline.

Fortunately, machine learning helps you continue providing online customer support through chatbots.

Through machine learning, chatbots can respond to complaints and answer queries like a human being would.

They can even give relevant answers because they learn how humans behave and interact.

Here’s an example by LiveChat:

                                                                                                                              Image Source: LiveChat

LiveChat chatbots can analyze the sentences, so they know what your customers are asking for. 

From keywords, product, and user information, etc. stored in their memory, they can answer FAQs and interact intelligently.

They can even speak the way humans do. Your customers might not even know they were talking to a robot.

Chatbots help you be more efficient because they allow you to automate your live chat 24/7. 

Automating your live chat enables you to focus on other important matters without worrying about your customer support.

3. Machine Learning Optimizes Emails for Marketing.

Machine learning optimizes your emails in many ways to help you convert your leads into customers.

It helps you personalize your emails and promotional offers, automate the delivery and split testing of emails, and more.

One machine learning tool, for instance, is Phrasee. 

                                                                                                                                         Image Source: Phrasee

Phrasee uses machine learning algorithms to enhance the language employed in your email subject lines.

Taking off from your campaign name, Phrasee creates and proposes subject lines, and lets you pick which one you liked best.

It even automates split tests for these subject lines for you to see which ones yield the best results.

By split testing, a million subject lines and measures the responses made, the learning machines of Phrasee can predict which language and emotion will garner the most clicks and opens.

When that happens, you can get more conversions and sales for your business.

4. Machine Learning Recommends Intelligently.

Machine learning continually learns from truckloads of data it obtains. 

That is why it can intelligently provide recommendations that are tailored-fit for your customers.

Take, for example, eBay. I clicked on a powder pink hoodie sweatshirt for women, and it recommended these items below:

eBay uses machine learning algorithms to identify products in listings, discover similar items, and rank its suggestions.

As such, it suggested other hooded sweatshirts but in different colors: magenta, grey, and blue-green, among others. 

When your customers see these recommendations, they will be enticed to explore them because they feel that the items still suit their preferences and interests.

They will then consider adding these items to their cart or choosing them instead of the first selection.

Machine learning makes intelligent recommendations useful because they are not based on random and unrelated feedback but real customer data.

Personalized recommendations, in this way, help you boost your sales and conversions.

Learn Machine Learning Now.!

In this age of AI, there’s never a better time to learn machine learning than now.

Many machine learning technologies have emerged, giving you more reasons to study their capabilities yourself (and the ones listed are only some of those reasons).

Studying these capabilities allows you to tailor-fit them according to your specific business needs. Machine learning can also give you a significant edge over your competitors.

Think this post was helpful? Do share it with your colleagues. Cheers!

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