ChatGPT seems like the ultimate get-out-of-work-free card. It can help you launch a <a href="https://twitter.com/rowancheung/status/1615768507421020161" style="color: #14aaed;">million-dollar-grossing</a> business, write a <a href="https://twitter.com/gregisenberg/status/1629158318915653633" style="color: #14aaed;">stern payment reminder</a> for an overdue client, and even <a href="https://twitter.com/greggyb/status/1631121912679002112" style="color: #5b6379;">code</a>. OpenAI, the company behind ChatGPT, is selling the dream of optimal results with minimal effort.
It’s divisive, to say the least. Fans of the artificial intelligence program are elated at the prospect of ChatGPT transforming (and upending) the landscape of written work, from CX interactions to marketing copy. Generative AI is the future, they say. Some have joked that ChatGPT’s intelligence is a bit too human-like, as this <a href="https://www.reddit.com/r/ProgrammerHumor/comments/11aki4z/well_that_escalated_quickly_chatgpt/" style="color: #14aaed;">satirical job post</a> for a “killswitch” position suggests. All said, it seems like an incredibly powerful tool. But when do ChatGPT’s talents hit a wall?
First let’s talk about what makes ChatGPT impressive.
The team at OpenAI, riding the high of the public’s excitement and a huge influx of <a href="https://blogs.microsoft.com/blog/2023/01/23/microsoftandopenaiextendpartnership/" style="color: #14aaed;">cash from Microsoft</a>, is pushing the narrative that there’s very little ChatGPT can’t do, and that its capabilities will only improve. More data to analyze will lead to more accuracy. Perfection (and human-like intelligence) seems to be just a matter of time.
When it comes to specific claims about what ChatGPT can do…
<ul style="font-size: 19px;">
<li style="line-height: 28px;">It can answer questions you’d usually Google, providing a more succinct, digestible result than a typical search engine. Instead of being given a list of webpage results, ChatGPT spits out a pithy paragraph to explain. If you have follow-up questions, you can ask them.</li>
<li style="line-height: 28px;">OpenAI reps claim that ChatGPT is the ultimate writing tool, capable of crafting ebooks and reports on any given topic. If true, this would free up a lot of time in the writing process. Research, outlining, and drafting would be reduced to nil. The idea is that you’d only have to set aside time for editing ChatGPT’s draft. Marketing materials like company sponsored ebooks and blog posts could be outsourced to AI, rather than copywriters on staff.</li>
<li style="line-height: 28px;">ChatGPT also appears capable of writing code. This raises the possibility of organizations outsourcing software development to AI, now or in the future as the program evolves.</li>
</ul>
Given these large claims, and some promising real-world uses, ChatGPT appears to be a resource with huge potential.
Like any tool, we need to understand ChatGPT’s limitations before we can get the most out of it. So let’s take a look at some of its biggest shortcomings, because despite what OpenAI’s fanbase would like you to think, ChatGPT does have some pitfalls.
<ol style="font-size: 19px;">
<li>
ChatGPT lies without realizing it By its own admission, ChatGPT has no idea if what it says is true. In its own words:
<div align="center" style="font-size:19px; line-height: 28px; font-weight:700">“I strive to provide accurate and helpful information to the best of my ability. However, it's important to note that the accuracy of my responses depends on the accuracy and completeness of the information that has been presented to me. If the information provided to me is inaccurate or incomplete, my responses may reflect that.” [emphasis mine] </div>
ChatGPGT relies on analyzing common responses to the words found in your prompt. In other words, it depends on data humans themselves have written. When AI synthesizes enough inaccurate information, it will generate inaccuracies. This gets at something Ezra Klein discussed on his <a href="https://www.nytimes.com/2023/01/06/podcasts/transcript-ezra-klein-interviews-gary-marcus.html" style="color: #14aaed;">podcast</a> with AI researcher Gary Marcus: yes, it can be handy to use ChatGPT in lieu of a Google search, but the information it generates could be entirely wrong. Relying on ChatGPT for information about medical concerns, for example, can have dangerous results.
And what makes the situation so tricky is that when humans say things that aren’t true, there are usually tells. Garbage information often sounds like garbage. But ChatGPT has the uncanny ability to make false information sound believable because its tone is confident. And that can be enough for some people to take ChatGPT’s words at face value. Don’t be duped!
</li>
<li>
ChatGPT fails at creativity Nothing ChatGPT says is original. Because it relies on material humans have created, everything it writes is derivative, literally derived from someone else’s work, without giving them credit. There’s <a href="https://www.forbes.com/sites/joemckendrick/2022/12/21/who-ultimately-owns-content-generated-by-chatgpt-and-other-ai-platforms/?sh=6ef629c25423" style="color: #14aaed;">some debate</a> about whether this constitutes plagiarism or intellectual theft. But regardless if it’s unethical, it’s bad for business.
Think about your org’s strategy for things like sales, marketing, or branding. What makes the copy effective? Chances are your copy is (or should be) showcasing the unique qualities of your product and targeting the unique desires of your prospect. Effective sales sets your offerings apart from the competition and hones in on your ideal consumer. Effective branding tells a story that is special to your company and your mission.
These are specific details you cannot replicate with generalized copy derived from other people. This means ChatGPT is ineffective for marketing or sales copy. Its stories are not compelling. Its marketing falls flat. Its sales will only work on people who aren’t picky about the products they buy and services they use, and which vendors they get them from—one-time customers who are not likely to become brand loyalists you can depend on.
</li>
<li>
ChatGPT’s code is nonsense When it comes to code, ChatGPT can be useful, but it can also generate downright gibberish. While the program appears capable of writing brief lines of code in just about any language (and has some <a href="https://twitter.com/amasad/status/1598042665375105024?ref_src=twsrc%5Etfw%7Ctwcamp%5Etweetembed%7Ctwterm%5E1598042665375105024%7Ctwgr%5E5925326e5fe1e9289839c37c08d3bb86de5ff1eb%7Ctwcon%5Es1_&amp;ref_url=https%3A%2F%2Fcdn.embedly.com%2Fwidgets%2Fmedia.html%3Ftype%3Dtext2Fhtmlkey%3Da19fcc184b9711e1b4764040d3dc5c07schema%3Dtwitterurl%3Dhttps3A%2F%2Ftwitter.com%2Famasad%2Fstatus%2F1598042665375105024image%3Dhttps3A%2F%2Fi.embed.ly%2F1%2Fimage3Furl3Dhttps253A252F252Fabs.twimg.com252Ferrors252Flogo46x38.png26key3Da19fcc184b9711e1b4764040d3dc5c07" style="color: #14aaed;">debugging abilities</a>), it can also go off the rails, suggesting solutions that don’t exist. Take a look at <a href="https://medium.com/@tanyamarleytsui/coding-with-chatgpt-b50ab3fcb45f" style="color: #14aaed;">this example</a>, where a software developer asks ChatGPT to write code in Python for spatial data analysis:
<div align="center" style="font-size:19px; line-height: 28px; font-weight:700">“I was quite impressed with the response, especially its suggestion to use gpd.gridify(), a geopandas attribute I’ve never heard of before. However, when I tried to run the code, I found out that the module geopandas has no attribute gridify. In other words, the chat bot suggested for me to use a tool that looks really handy, but doesn’t actually exist.”</div>
ChatGPT’s code doesn’t work because it makes up an attribute that doesn’t exist. When the human programmer tries to correct ChatGPT, it digs in its heels and insists that the human expert is mistaken. The author concludes that the goal of AI tools like ChatGPT is to mimic the appearance of truth, without necessarily being true.
This judgment is echoed by other software developers on <a href="https://news.ycombinator.com/item?id=33861846" style="color: #14aaed;">discussion boards</a>:
<div align="center" style="font-size:19px; line-height: 28px; font-weight:700">“This is the scary thing about this - I keep asking it questions, and it gives confident, lengthy responses that look perfect. But when you read it thoroughly, you start noticing small but important mistakes that are not obvious at first.”</div>
ChatGPT’s coding abilities amount to appearing plausible but having big problems.
</li>
</ol>
These things are currently outside ChatGPT’s abilities: saying things that are true, writing unique copy, and coding. Now that we have a handle on the things ChatGPT can’t reliably do, we can explore tasks ChatGPT can be useful for.
Stay tuned for a follow-up on ChatGPT’s best uses and other AI tools that can aid productivity. Want to be notified? Sign up for <a href="https://www.jobsity.com/blog" style="color: #5b6379;">our blog newsletter</a>.
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ChatGPT seems like the ultimate get-out-of-work-free card. It can help you launch a million-dollar-grossing business, write a stern payment reminder for an overdue client, and even code. OpenAI, the company behind ChatGPT, is selling the dream of optimal results with minimal effort.

ChatGPT: What Can’t It Do?

Whether you’re just starting your career as a software developer or you’re a seasoned pro looking to branch out, here are some of trending coding languages for 2023.
<h2 style="font-size: 24px;">JavaScript</h2>
Career goal: JavaScript is a great scripting language for someone interested in front-end web development, back-end web development, and mobile app development.
History: Released in 1995, JavaScript allows coders to create dynamic content. Note that JavaScript is not the same as the language Java.
Uses: With dynamic, single-page webpages increasing in popularity, JavaScript remains a popular language in the coder’s toolbox. About<a href="https://javascript.plainenglish.io/should-you-use-javascript-for-everything-f98015ade40a"> 98% of websites</a> use JavaScript for front-end development. If you want to use JavaScript to develop back-end applications, you can use Node.JS, a JavaScript runtime, to make that possible.
Upsides: It’s a great foundational skill. JavaScript has flexible, forgiving syntax, so it’s relatively easy to learn and apply in a variety of contexts.
Challenges: A pitfall to watch out for is that JavaScript’s code can be interpreted differently on different browsers.
Where you’ve seen it: Facebook, Twitter, Gmail, Youtube, and other websites that offer dynamic interfaces.
<h2 style="font-size: 24px;">Python</h2>
Career goal: Python can be an awesome language to pick up if you’re interested in back-end web development, creating desktop apps, or developing machine learning programs.
History: Python has a bit of an unusual creation story. It was released in 1991 by<a href="https://pythoninstitute.org/about-python#:~:text=Python%20was%20created%20by%20Guido,called%20Monty%20Python's%20Flying%20Circus."> Guido van Rossum</a>, an individual developer, rather than a team. Now, however, Python has been built on by numerous people across the globe, thanks to it being an open source language.
Uses: Python was created to be fast to pick up. Beginners can feel confident choosing it as a first language. Its syntax feels akin to English and its very intuitive to write code in. Python is also designed to provide a more efficient coding experience.
Upsides: Because it's an open source project, Python users enjoy lots of community support and abundant resources, like libraries and frameworks. It also easily integrates with web services, making it especially versatile.
Challenges: Keep in mind that if you want to develop mobile applications, Python is not the language for you.
Where you’ve seen it: You’ve likely encountered Python when using certain features on Youtube, Reddit, and Dropbox.
<h2 style="font-size: 24px;">Go</h2>
Career goal: Aiming for a career in data science, systems programming, desktop app development, or back-end web development? Go is for you.
History: Go (also referred to as Golang) was publicly released by Google in 2009 and made open source in 2012. The goal was to create a coding language<a href="https://www.freecodecamp.org/news/what-is-go-programming-language/"> more straightforward and efficient</a> than C++.&nbsp;
Uses: Go provides similar functionality to C and C++ without the tricky syntax and learning curve. Go’s simple approach to systems programming has made it a popular choice among developers of all experience levels.
Upsides: Go’s benefits include great scalability, concurrency, and a crazy fast runtime. It’s also useful for managing large codebases, developing web servers, data pipelines, and machine learning programs.
Challenges: Go isn’t the most versatile coding language out there, and it doesn't come with much library support.
Where you’ve seen it: Go is used by major companies like Google (its creator), Uber, and Twitch.
<h2 style="font-size: 24px;">Java</h2>
Career goal: Java is a key language for anyone looking for jobs in web application development, particularly for large-scale apps. Interested in working with big data? Java is also a great choice for that specialty, as well.
History: Java was released in 1991 and was designed to help make the World Wide Web<a href="https://www.britannica.com/technology/Java-computer-programming-language"> more interactive and feature multimedia</a>. Note that Java is distinct from JavaScript. JavaScript runs in web browsers and is intended to be a companion to Java.
Uses: Java was created with the intention that a coder can “write once, run anywhere.” Code written in Java can be portable across diverse platforms, making it a language with a lot of versatility. And because it’s object-oriented, it can be used to create a wide variety of apps.
Upsides: Compared to other interpreted languages, Java runs quickly and efficiently. When coding in Java, you also have an abundance of frameworks and libraries to choose from, thanks to robust community user support.
Challenges: The main pitfall of Java is that, while it’s faster than other interpreted languages, it still runs slower than natively compiled languages, like C++.
Where you’ve seen it: Java is used for backend management for Google, Amazon, Twitter, and YouTube.
<h2 style="font-size: 24px;">C#</h2>
Career goal: C# (pronounced “C sharp”) is one of the best programming languages to learn for coders looking to get into game development, virtual reality programs, and Windows desktop applications.
History: The first version of C# was<a href="https://learn.microsoft.com/en-us/dotnet/csharp/whats-new/csharp-version-history"> released in 2002 by Microsoft</a>. It’s intended to support object-oriented programming and is commonly used alongside the .NET framework.
Uses: C# is incredibly powerful. It can be used to develop all sorts of apps for a variety of purposes—like video games and cloud services—and for diverse platforms. It’s the recommended language when developing 2D and 3D games.
Upsides: C# performs well due to the<a href="https://www.ibm.com/docs/en/sdk-java-technology/8?topic=reference-jit-compiler"> JIT (Just-In-Time) compiler</a> and its solid runtime environment. And thanks to it’s garbage collection and asynchronous programming capabilities, C# developers can write efficient and scalable code.
Challenges: C# is less flexible and forgiving than C++. It also takes a lot of time and effort to learn, so it's not a great choice if you want to start writing code quickly! And if you run into an error in your C# code, it can take a lot of experience to be able to locate and fix it.
Where you’ve seen it: Applications developed for the likes of Windows, Android, and iOS have been written with C#.
<h2 style="font-size: 24px;">Swift</h2>
Career goal: Eager to create applications for iPhones, Apple watches, and Macs? Swift is a great coding language to choose.
History: Swift was developed<a href="https://www.techrepublic.com/article/apples-swift-programming-language-the-smart-persons-guide/"> by Apple in 2014</a> for Apple and Linux platforms.
Uses: Like many products created by Apple, Swift has a reputation for being more secure than its alternatives. This means that, ideally, apps created with Swift are less vulnerable to hacking and malicious interference.
Upsides: Swift is a very beginner-friendly language that doesn’t require much previous coding experience. It’s also open source, so you can get started learning it right away. On top of that, it has a lightning-fast runtime.
Challenges: Because Swift is a relatively new language, it can be a little unstable. It also lacks robust user support, resources, and an online community. If you feel comfortable fending for yourself a bit, Swift can be a great coding language to add to your resume.
Where you’ve seen it: Many popular iOS apps, like Instagram and Soundcloud’s mobile app interfaces, were created using Swift.
<h2 style="font-size: 24px;">Ruby</h2>
Career goal: If you’re looking to launch a career in back-end web development, Ruby is a solid choice.
History: Ruby is an object-oriented programming language. It was was publicly released in 1995 by creator Yukihiro “Matz” Matsumoto. Matz’ goal was to create<a href="https://www.ruby-lang.org/en/about/"> a language that mimics life</a>—deceivingly simple on the surface, with lots of complexity the deeper you look.
Uses: Ruby’s simple syntax makes it easy to edit code down the line. It also has a reputation for good security and has solid garbage collection.
Upsides: Learning Ruby comes with lots of benefits. It’s an open source language with an active, supportive community (they even have conferences!), so you won’t be on your own if you encounter challenges. Thanks to Ruby’s human-friendly syntax and object-oriented design, it’s also relatively easy to learn.
Challenges: While it’s fast to write code in, Ruby programs can be slow to run. Ruby also adheres to a very specific set of rules; there’s very little room for flexibility.
Where you’ve seen it: Major businesses like AirBnb and Shopify have used Ruby alongside the Rails framework (“Ruby on Rails”) to build their websites.
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Whether you’re just starting your career as a software developer or you’re a seasoned pro looking to branch out, here are some of trending coding languages for 2023.

The 7 Best Coding Languages to Learn in 2023

Pair programming is a popular method some companies use to improve the coding skills of their software development staff. But is it all it’s cracked up to be?
<h2 style="font-size: 23px;">What is Pair Programming?</h2>
Let’s get a clear picture of what pair programming is.
You have a pair of developers working together, each in a different role: one “driver” who writes the code and one “navigator” who reviews the code and maintains a sense of direction for the coding session. Both people are working alongside each other, and they periodically switch roles. The goal is that, since the work is being reviewed in real time, the code quality will improve.
Traditionally, pair programming can be done “hip to hip,” with the driver and the navigator sitting very close to each other, sharing a monitor. Of course, this physical set-up is a bit cramped! Nowadays, pair programming is typically done with screen sharing or remote desktop access, so that the devs don’t have to sit so close together, or even work from the same location! In other words, pair programming is accessible to remote staff and distributed teams.
Some developers feel strongly that, while pair programming can be a great tool<a href="https://levelup.gitconnected.com/4-ways-pair-programming-can-hurt-you-dbb3b0fab19a"> when used intentionally</a> in specific circumstances, it may be a<a href="https://hackernoon.com/we-need-to-abolish-pair-programming-pl7z35bv"> horrible method to use across the board</a>, as a teamwork default. Time for a pros and cons comparison! Let’s look at the upsides of pair programming, and then cover its common criticisms.
<h2 style="font-size: 23px;">Upsides</h2>
<h3 style="font-size: 19px;">1. Two heads are better than one</h3>
When you work independently on a problem, you are limited by the bounds of your own creativity and knowledge. And when you stare at a problem for long enough, it becomes more difficult to see the situation in a new, creative light. In other words, someone else will be able to see options and roadblocks that you don’t. This is called the<a href="https://www.interaction-design.org/literature/topics/einstellung-effect"> Einstellung Effect</a>: the longer you look at a problem, the less creatively you approach it.
With pair programming, the Einstellung Effect is less of a concern because you’re working alongside another person who gives feedback on your code, and you give feedback on theirs.<a href="https://betterprogramming.pub/5-huge-benefits-of-pair-programming-7d30076e0c25"> Two heads</a> are better than one! If you’re working independently, we recommend setting a limit to the amount of time you work solo, to avoid getting stuck for too long.
<h3 style="font-size: 19px;">2. Learn from each other</h3>
Programming in a pair also helps you learn new coding methods, strategies, and shortcuts because you’re observing how someone else does their work.
And it’s more effective than someone sharing their tips and tricks with you just by explaining them, because you get<a href="https://hackernoon.com/benefits-of-pair-programming-s51a3ur8"> hands-on practice</a>! So the things you pick up are more likely to stick and help you improve your own coding game in the long run.
<h3 style="font-size: 19px;">3. Gain institutional knowledge from a seasoned expert</h3>
For new staff, it can be super useful to pair program with an experienced member of the team. This can be a form of onboarding or temporary mentorship. The new dev will more quickly learn where things are, how to access certain resources, and the best methods for addressing certain company challenges. Using pair programming as part of the onboarding process can be great.
<h3 style="font-size: 19px;">4. Prevent siloing</h3>
When everyone on a team works independently, this can lead to knowledge siloing: no one knows what other people know. This means that when you lose a<a href="https://www.codecademy.com/resources/blog/what-is-pair-programming/"> “tower of knowledge”</a>, even temporarily, you lose their expertise.
Pair programming curtails this issue because it involves sharing knowledge and methods across team members. When multiple people know how something works, your team has more sources of wisdom when one particular person isn’t available.
<h3 style="font-size: 19px;">5. Increase camaraderie</h3>
Pair programming<a href="https://betterprogramming.pub/5-huge-benefits-of-pair-programming-7d30076e0c25"> helps teammates bond</a>, especially in a remote work environment. In the age of awkward virtual coffee hours, shared projects help us connect with each other in a more comfortable, authentic way.
<h2 style="font-size: 23px;">Downsides</h2>
Of course, there are some downsides to pair programming that can make it difficult to rely on.
<h3 style="font-size: 19px;">1. Interruptions</h3>
First, a lot of the coding process relies on uninterrupted focus. While this is true of all career types, it is especially important that we let our coders get into a flow state if we want them to be efficient.<a href="https://hackernoon.com/we-need-to-abolish-pair-programming-pl7z35bv"> Disruptions</a> to the coding process make it<a href="https://levelup.gitconnected.com/4-ways-pair-programming-can-hurt-you-dbb3b0fab19a"> inefficient</a>, and unfortunately, pair programming can be a heap of disruption!
Collaboration can be helpful, but only to a point. There comes a time when two programmers could be working on different projects independently, instead of working more slowly on one shared project.
Solution: Consider why you think pair programming would be useful for a particular project or set of coders. You need to be clear on your objectives! Why are you choosing a slower process (pair programing) over a faster one (working independently)? Once you’re clear on the reasons, set a limit to how much time the coders will spend pair programming, so that the project isn’t ground to a halt.
<h3 style="font-size: 19px;">2. Hand-holding</h3>
There’s also the issue of some staff using pair programming as a<a href="https://levelup.gitconnected.com/4-ways-pair-programming-can-hurt-you-dbb3b0fab19a"> crutch</a> for their work. Having a self-starter attitude is essential in software development, so if someone isn’t comfortable working by themselves, it’s a problem. Don’t let pair programming become an everyday work style for the same staff members, over and over again.
Solution: your org needs to have a culture of go-getterness and empower everyone to contribute equally, according to their talents. If a team member seems overly reliant on pair programming, check in with them to ask what’s going on. It’s possible they're lacking confidence in their skills and need to be reminded of their value, or they might just enjoy the company of their programming partner and need to manage social time vs. work time better.
<h3 style="font-size: 19px;">3. Poor attitudes</h3>
With pair programming, it’s possible that not everyone will be<a href="https://levelup.gitconnected.com/4-ways-pair-programming-can-hurt-you-dbb3b0fab19a"> a good sport</a> about it. Pair programming requires openness to collaboration and working at a slower pace. For some coders, this situation is a nightmare, and they want no part in it. Don’t force them!
It brings down morale when one person is willing to pair program and the other isn’t. The first person might feel socially rejected and the second person could become frustrated. If this dynamic becomes the norm, it could hurt company retention. And of course, a stubborn attitude from one programmer can further slow down the project.
Solution: You should only pair programmers who are excited to collaborate. And if pair programming is important to the goals of your org, get more people onboard with the work style by encouraging a culture of constant collaboration, outside of pair programming. If a team is more comfortable sharing ideas and giving feedback, they will probably be more open to pair programming, even temporarily.
<h3 style="font-size: 19px;">4. No growth</h3>
It’s possible that the paired programmers<a href="https://levelup.gitconnected.com/4-ways-pair-programming-can-hurt-you-dbb3b0fab19a"> might not learn anything</a> from the process, in which case, the paired setup was a waste of time.
Solution: In order for pair programming to be most effective, you need to have one of two situations:
<ol style="font-size: 19px;">
<li style="color: #000000;" aria-level="1">The partners need to be learning from each other, or</li>
<li style="color: #000000;" aria-level="1">One person needs to be mentored by another, with the second person working on their mentorship skills.</li>
</ol>
In other words, there should be some difference in the partners’ individual knowledge bases and experience level. To make this dynamic possible, avoid partnering people who have near-identical skill sets and work backgrounds.
<h2 style="font-size: 19px;">Conclusion</h2>
While pair programming can be a slower coding strategy, more work up front can save you time in the long run. If you’re clear on why you want to implement pair programming and you find good partnerships, the strategy can improve your team’s workflow.
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Pair programming is a popular method some companies use to improve the coding skills of their software development staff. But is it all it’s cracked up to be?

Pair Programming: Tech's Best Friend or Biggest Nightmare?

When it comes to the booming tech hiring market, it pays to stand out from the crowd. If you’re looking for jobs in 2023, here are some great, in-demand skills to invest in.
<h2 style="font-size: 23px;">Data Science</h2>
<h3 style="font-size: 19px;">What it is</h3>
Data science is a hybrid field that requires you to integrate multiple areas of knowledge into your work: data analytics, statistics, strategic planning, strong communication, and more, depending on the industry you work in. The main purpose of data science is to help your organization interpret data trends and advise leadership on a course of action.
While the role of a data scientist might overlap with a data analyst, the jobs differ in terms of breadth. A data scientist spends more time than an analyst creating visualizations and statistical interpretations, and they must be able to communicate their interpretations and strategic recommendations in language that’s easy for company leadership to understand.
<img src="https://5621549.fs1.hubspotusercontent-na1.net/hubfs/5621549/img-blog_1_1_-png.png" loading="lazy" width="677" height="554" style="width: 677px; height: auto; max-width: 100%; margin-left: auto; margin-right: auto; display: block;">
<h3 style="font-size: 19px;">Why it’s useful</h3>
Because there are so many new ways of collecting and organizing data, we have access to more information than ever before. This means data science is becoming increasingly in-demand to all kinds of businesses.
Data scientists can analyze information in different ways and use it for different purposes. For example, you might interpret data to…
<ul style="font-size: 19px;">
<li style="color: #000000;" aria-level="1">understand what is currently happening (descriptive analysis)</li>
<li style="color: #000000;" aria-level="1">what the causes are (diagnostic analysis)</li>
<li style="color: #000000;" aria-level="1">what could happen in the future (predictive analysis)</li>
<li style="color: #000000;" aria-level="1">and what the best course of action is (prescriptive analysis)</li>
</ul>
Here are some real-world examples of how data science has been used in various industries:
<ul style="font-size: 19px;">
<li style="color: #000000;" aria-level="1">Shanghai Changjiang Science and Technology Development relied on data scientists to help build an AI program that assesses patient medical records to determine their risk of stroke. The program also determines which treatment plan will have the greatest chance of success.</li>
<li style="color: #000000;" aria-level="1">The<a href="https://about.ups.com/us/en/newsroom/press-releases/innovation-driven/ups-to-enhance-orion-with-continuous-delivery-route-optimization.html" style="color: #000000;"> shipping company UPS</a> uses data science to optimize mail delivery and transportation, specifically by determining which routes are the most fuel-efficient and least impacted by traffic.</li>
<li style="color: #000000;" aria-level="1"><a href="https://www.whoop.com/" style="color: #006dca;">Exercise company WHOOP</a> developed a wearable fitness device that tracks the user’s heart rate, blood oxygen levels, and sleep quality. The device interprets this data to make recommendations for rest, increased activity, and more.</li>
</ul>
Given how important it is to understand market trends and company performance, data scientists play a critical role in the success of their organizations. Consider becoming one if you want to help leadership interpret data and form strategic plans!
<h2 style="font-size: 23px;">Cloud Computing</h2>
<h3 style="font-size: 19px;">What it is</h3>
Cloud computing offers resources like file storage, servers, and software via the internet access (the “cloud”), rather than having to store these items locally in a physical location you have access to. Just about everyone relies on cloud computing in some capacity.
<img src="https://5621549.fs1.hubspotusercontent-na1.net/hubfs/5621549/img-blog_1_2_-png.png" loading="lazy" width="573" height="469" style="width: 573px; height: auto; max-width: 100%; margin-left: auto; margin-right: auto; display: block;">
<h3 style="font-size: 19px;">Why it’s useful</h3>
Many digital tools and services we use—like data backups, email, software development, analytics, and virtual desktops—run on cloud computing.
Cloud computing’s popularity is due to unique benefits like increased program agility, lower costs, and easier scalability. These factors make cloud computing very attractive to companies looking to save costs, adapt to changing needs, and scale in a sustainable way—in other words, just about everyone.
Here are some examples of how cloud computing is being used in different industries:
<ul style="font-size: 19px;">
<li style="color: #000000;" aria-level="1"><a href="https://about.netflix.com/en/news/completing-the-netflix-cloud-migration" style="color: #006dca;">Media streaming</a>: When you listen to music on Spotify or watch a show on Netflix, you’re accessing content stored on the companies’ cloud servers.</li>
<li style="color: #000000;" aria-level="1"><a href="https://www.google.com/drive/" style="color: #006dca;">File storage</a> &amp;<a href="https://www.dropbox.com/features/cloud-storage" style="color: #000000;"> sharing</a>: when you add files to your Google Drive or Dropbox folder, you’re uploading them to the organizations’ cloud storage. These files can then be accessed from a different device, freeing up space on your local hard drive and making them instantly viewable whenever you (or someone you’ve shared access with) have an internet connection.</li>
<li style="color: #000000;" aria-level="1">Cybersecurity: businesses like Forcepoint rely on a<a href="https://info.forcepoint.com/forcepoint-one-demo/?_bt=591923099491&amp;_bk=forcepoint&amp;_bm=e&amp;_bn=g&amp;_bg=66466825153&amp;sf_src_cmpid=77015f0000001Q8L&amp;utm_term=forcepoint&amp;utm_campaign=NAM_-_BRN_-_Brand_Terms_-_Search&amp;utm_source=google&amp;utm_medium=search_pd&amp;utm_content=brand_terms_search_cam=770037328&amp;hsa_acc=4948252953&amp;hsa_cam=770037328&amp;hsa_grp=66466825153&amp;hsa_ad=591923099491&amp;hsa_src=g&amp;hsa_tgt=kwd-318146607759&amp;hsa_kw=forcepoint&amp;hsa_mt=e&amp;hsa_net=adwords&amp;hsa_ver=3&amp;gclid=EAIaIQobChMItOy-spvS_AIVVB-tBh3GgQEWEAAYASAAEgJQZfD_BwE" style="color: #000000;"> “Cloud Access Security Broker”</a> to help provide cutting edge protection to their clients’ digital assets and information.</li>
<li style="color: #000000;" aria-level="1">Just about any company that offers IaaS, PaaS, or SaaS—Infrastructure-as-a-Service, Platform-as-a-Service, and Software-as-a-Service, respectively—depends on cloud computing.</li>
</ul>
As cloud-based services and products become more popular, developers knowledgeable in cloud computing will be in higher demand, too.
<h2 style="font-size: 23px;">Machine Learning</h2>
<h3 style="font-size: 19px;">What it is</h3>
Machine learning is a new professional field that integrates computer science with artificial intelligence. A program built with machine learning is essentially mimicking how humans learn—by learning and growing from their mistakes. With machine learning, you can design a program that trains itself to become more accurate over time.&nbsp; This makes machine learning a subfield of artificial intelligence, along with related specialties like deep learning and neural networks.&nbsp;
<img src="https://5621549.fs1.hubspotusercontent-na1.net/hubfs/5621549/img-blog_1_3_-png.png" loading="lazy" width="568" height="343" style="width: 568px; height: auto; max-width: 100%; margin-left: auto; margin-right: auto; display: block;">
<h3 style="font-size: 19px;">Why it’s useful</h3>
Machine learning has proliferated just about every major industry. It’s time-consuming and difficult for programmers to create a piece of software that produces human-like results. Instead, machine learning allows coders to create software that’s able to reprogram itself as it gains data from its experiences.
Machine learning depends on skills like statistics and algorithm development, which help the program practice identifying and responding to data (like words or images). Like with data science, the insights gained from machine learning can help organizations make decisions about their products/services, internal culture, business strategy, and more.
Here are some examples of how machine learning is being used all around us:
<ul style="font-size: 19px;">
<li style="color: #000000;" aria-level="1"><a href="https://bakeryscan.com/bakeryscan-eng/" style="color: #006dca;">BakeryScan</a> is an AI-operated camera that identifies which pastries a customer has selected, then calculates the total money owed. Its software is being<a href="https://www.newyorker.com/tech/annals-of-technology/the-pastry-ai-that-learned-to-fight-cancer" style="color: #000000;"> adapted to other contexts</a> like hospitals and aircraft assembly warehouses.</li>
<li style="color: #000000;" aria-level="1">Predictive text, like the<a href="https://developer.apple.com/design/human-interface-guidelines/technologies/machine-learning/roles/" style="color: #000000;"> QuickType</a> recommendations you see when responding to a friend’s iMessage, depend on machine learning to identify and recommend what you usually say in similar contexts.</li>
<li style="color: #000000;" aria-level="1">Streaming recommendations, like<a href="https://medium.com/@springboard_ind/how-netflixs-recommendation-engine-works-bd1ee381bf81#:~:text=Netflix's%20machine%20learning%20based%20recommendations,and%20accurate%20the%20algorithm%20is." style="color: #000000;"> Netflix</a> suggesting movies you might enjoy, depend on machine learning. In Netflix’s case, the company collects data from its customers, identifies patterns in the content certain users enjoy, then makes recommendations to you based on the watch history of people with similar tastes.</li>
<li style="color: #000000;" aria-level="1">Unlike humans,<a href="https://aws.amazon.com/what-is/machine-translation/#:~:text=Machine%20translation%20is%20the%20process,text%20in%20the%20target%20language." style="color: #000000;"> translation</a> programs don’t learn the grammar and syntax of different languages. Instead, their responses rely on machine learning to analyze human translations and identify patterns. These patterns allow them to generate translations to program users.</li>
<li style="color: #000000;" aria-level="1"><a href="https://neptune.ai/blog/building-machine-learning-chatbots-platforms-and-applications" style="color: #006dca;">Chatbots</a>, commonly used to facilitate conversations with shoppers on retail websites, rely on machine learning to improve their responses to human customers.</li>
</ul>
Given how common it is to run into machine learning in your everyday life, it’s a great skill to invest in!
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If you’re looking to forge a new path in your tech career, consider developing your skills in data science, cloud computing, or machine learning. They're sure to be popular in the 2023 hiring market! As interest in these specialties grows, you can leverage your new skills to land a job that’s aligned with your professional goals! Remember: working in tech means constantly learning and upping your game.
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When it comes to the booming tech hiring market, it pays to stand out from the crowd. If you’re looking for jobs in 2023, here are some great, in-demand skills to invest in.

Three Trending Tech Skills for 2023

With organizations increasingly relying on digital tools like databases, servers, and APIs, backend security is of the utmost importance. From SQL injections, to distributed denial-of-service (DDoS), to credential stuffing, cyber attacks can come in many forms, and they are constantly evolving.
When we fail to prioritize digital security, we face multiple risks, from lost revenue to breached privacy to a compromised reputation. In 2020, over<a href="https://www.ideamotive.co/blog/backend-security-best-practices"> 155 billion people</a> were affected by data breaches in the United States alone. And regarding lost funds, IBM estimates that hacked data resulted in a loss of<a href="https://www.ideamotive.co/blog/backend-security-best-practices"> $3.86 billion</a> in 2020.
So what can we do to protect our data, customer privacy, and revenue? Let’s take a look at some solid practices that can keep your organization safe from cyber attacks.
<h2 style="font-size: 23px;">1. Isolate your databases and servers</h2>
First things first: isolate your databases and servers. Connected or linked systems make it easier for hackers to access more digital areas of your organization, because they can move between them laterally. If they can gain access to one of your less secure servers, they might be able to use that access to move into another part of your organization.
To prevent this, consider keeping servers on different machines and limit how many files are stored in shared environments. Isolating servers and databases means possible attacks will be more contained.
<h2 style="font-size: 23px;">2. Manage User Access Wisely</h2>
Cyber attacks don’t always come from external foes; hackers can be members of your own company, gaining your trust and getting access to powerful data. Always be aware of the possibility of internal threats.
With this in mind, consider using the<a href="https://www.f5.com/labs/learning-center/securing-apis-10-best-practices-for-keeping-your-data-and-infrastructure-safe"> “least privilege” principle</a> to govern who has access to what areas and how much access they have. In other words, limit how much access each staff member has to your digital information. Never give someone more access than they need in order to do their job.
We also recommend monitoring who is accessing sensitive databases, and when they do it. If you observe any unusual patterns (like someone viewing the data of a sector they don’t work in, or accessing data outside of normal work hours), this can tip you off to suspicious activity.
<h2 style="font-size: 23px;">3. Protect Login Credentials</h2>
Staff should also avoid sharing credentials with other organization members. If you absolutely must share credentials, never do so on a public network or without encryption. Public networks are especially vulnerable to hackers who can observe your digital activity. You don’t want them spying on you sending passwords to a coworker.
And when it comes to storing credentials, these files should never be viewable as plain text. Instead, be sure to encrypt them so they’re indecipherable to third parties. Always encrypt passwords.
When logging into an account, consider using secondary authentication and authorization solutions, in addition to passwords. Things like two-factor authentication (which can involve sending a verification code to your phone) help ensure the correct person is accessing the database. A simple password is not enough, because hackers have sophisticated ways of guessing our passwords.
<h2 style="font-size: 23px;">4. Anonymize your data</h2>
When doing analysis on data sets, it’s not necessary to know whose data is whose. To protect individuals’ privacy,<a href="https://medium.com/swlh/more-security-best-practices-for-backend-developers-c7a41f85bf8e"> anonymize data</a> before analyzing it. This means separating an individual’s identifying information (e.g. their name, address) from other data provided.
This helps maintain privacy within your organization, and it also means that if a third party gets unauthorized access to the data, the individuals’ privacy is still preserved.
<h2 style="font-size: 23px;">5. Throttle data capacity</h2>
Hackers sometimes use a method called a<a href="https://www.cloudflare.com/learning/ddos/what-is-a-ddos-attack/"> Distributed Denial of Service</a> attack. A DDoS attack involves someone attempting to overwhelm your server with too many requests for the server to handle. It might try to flood your site with excess traffic or submit a form an exponential number of times.
To prevent a DDoS attack, consider limiting the amount of data that a user can transmit to your site. For example, limit the number of times someone can submit a form in a set period of time, or throttle how many visitors can access your website at once.
Also consider limiting the number of times a user can attempt to log in (this will also protect you from hackers who auto-generate password guesses until they reach the correct one). This will protect your server from being overwhelmed and becoming vulnerable to forced entry.
<h2 style="font-size: 23px;">6. Upgrade your OS and apps</h2>
Third-party plugins, apps, and APIs can create vulnerabilities for your organization. This means cyber attackers can use them to get access to your digital infrastructure.
To limit the vulnerability that comes with using third-party apps, make sure all your software and plugins are up-to-date. All items you’ve installed should be running on their most recent version.
Also be sure to delete stuff you don’t use. Extra apps and plugins can clutter up your digital space and make things run slower—and also make you vulnerable to attacks. If you don’t use it, toss it.
<h2 style="font-size: 23px;">7. Implement data backups &amp; encryption</h2>
Finally, what are your organization’s failsafe measures? If a hack is successful, how will you limit the damage? Consider using encryption and backups.
Encryption is a protective measure that prevents hackers from understanding your data, even if they get their hands on it. And backups ensure that if your data is stolen or erased, you have another copy and haven’t lost all your information. These two measures can help prevent a hack from having catastrophic consequences.
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There you have it! Now you have a good foundation for protecting your organization from cyber attacks when it comes to backend security.
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With organizations increasingly relying on digital tools like databases, servers, and APIs, backend security is of the utmost importance. From SQL injections, to distributed denial-of-service (DDoS), to credential stuffing, cyber attacks can come in many forms, and they are constantly evolving.

Protecting Your Company with Backend Security

It’s no secret that American schools are struggling. Today’s K12 teachers face overwhelming workloads, large class sizes, and not enough staff support. And students are having a hard time, too. The COVID-19 pandemic has had negative effects on student success and wellbeing<a href="https://www.brookings.edu/blog/brown-center-chalkboard/2022/03/03/the-pandemic-has-had-devastating-impacts-on-learning-what-will-it-take-to-help-students-catch-up/#:~:text=Further%2C%20achievement%20tended%20to%20drop,the%20spring%202020%20school%20closures."> across the board</a>.
With these impacts on academic development, it has become harder to set students up for success in the long-term. University professors report that their recent freshmen classes have been<a href="https://twitter.com/Literature_Lady/status/1584646085452058625?s=20&amp;t=T-iRxXEwDZq6H74br8erag"> completely unfamiliar</a> with basic concepts they need in order to thrive in a college setting. This isn’t the educational experience we want for our communities.
Instead, we envision everyone, of all backgrounds, receiving an excellent education, where they’re shepherded through the learning process with personal care and attention. This type of learning experience would lead to improved grades and academic success across the board, with students succeeding in all K12 fundamentals.
And of course, we want our teachers to have reasonable workloads, so that they can bring their best, healthiest selves to the classroom. If their energy is protected and they don't feel exhausted, the quality of their teaching will also improve.
Modern tech advancements have given us innovative solutions for things like communication and transportation. Is there anything we can do to improve our learning environments? How can we make the ideal educational experience a reality? Artificial intelligence is a possible solution.
<h2 style="font-size: 23px;">Learning &amp; Teaching Better with AI</h2>
While digital learning can be viewed as a downgrade from in-person learning, modern technology can complement and improve in-person teaching.<a href="https://www.ibm.com/cloud/learn/what-is-artificial-intelligence"> According to IBM</a>, Artificial intelligence (AI) is a type of technology that can “mimic the problem-solving and decision-making capabilities of the human mind.” Given the increase in remote learning and digital education tools, schools may be more open to using AI now than they were before the pandemic. How can AI help us learn and teach better?
As a learning companion, one of AI’s greatest strengths is that it can<a href="https://www.forbes.com/sites/calumchace/2020/10/29/the-impact-of-artificial-intelligence-on-education/?sh=5866cb8f50df"> customize the educational experience</a> to each individual student. Digital tools like Adaptive Learning observe students’ unique struggles and learning patterns. Then it adapts to create<a href="https://www.linkedin.com/pulse/personalised-elearning-tailored-pathways-ryan-o-connell/"> custom, targeted teaching strategies</a> for each student.
For students who need greater support, AI can generate “smart content” like flash cards, quizzes, and practice tests. AI can also serve as a personal tutor that dialogues with students.
AI can also assist with teaching workloads. To help teachers get back to the most important aspect of their job—providing personal guidance for students’ learning journeys—AI programs can automate the more mundane, routine aspects of teachers' jobs.
In a study published by The Telegraph, educators say that only <a href="https://www.telegraph.co.uk/news/2019/07/21/teachers-spend-time-marking-planning-classroom-ofsted-survey/">43% of their time</a> is spent teaching, while more than 30% is used for things like administrative work and lesson planning. AI can free up this time for teachers, so they can focus on the most important functions of their work.
Ai could perform tasks like providing auto-responses to students' common questions, or grading test portions that are multiple-choice or Y/N based. AI could also provide feedback for teachers based on observations of student performance. For example, if most students struggle with the same type of question, AI could tell the instructor to revisit the lesson and brainstorm new ways to teach it.
The modern advances of AI also make educational content more broadly accessible. For example, by auto-generating translated captions, a lecture originally presented in English could be made available to interested people who speak other languages.
<h2 style="font-size: 23px;">The Limitations of AI in the Classroom</h2>
If there are so many potential benefits of using AI for education, are there any drawbacks? The biggest potential concern is that schools may try to use AI to replace teachers altogether. But this would definitely backfire, since AI cannot replace a human’s personal attention and care for students. We still require human teachers!
AI is also fallible. There are times when it slips up or makes mistakes. AI doesn’t have common sense, and sometimes it lacks the necessary context to make a good decision. So in order to use AI the best way in a classroom, it should support educators, instead of replacing educators altogether.
Innovations in technology can improve all aspects of our lives, if done well. Artificial intelligence has the potential to provide custom tutoring exercises to students, make teachers’ workloads more reasonable, and make learning materials accessible to broader audiences. A better school experience for everyone!
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It’s no secret that American schools are struggling. Today’s K12 teachers face overwhelming workloads, large class sizes, and not enough staff support. And students are having a hard time, too. The COVID-19 pandemic has had negative effects on student success and wellbeing across the board.

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