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Monthly Archives: August 2023
The Role of Artificial Intelligence in Enhancing Forensic and … – Fagen wasanni
Posted: August 10, 2023 at 7:24 pm
Exploring the Impact of Artificial Intelligence on Forensic and Genealogical Investigations
Artificial Intelligence (AI) is revolutionizing various sectors, and the fields of forensic and genealogical investigations are no exception. The integration of AI into these areas is not only enhancing the accuracy of investigations but also significantly reducing the time taken to reach conclusions.
In the realm of forensics, AI is playing a pivotal role in transforming traditional investigative methods. Forensic investigations often involve the analysis of vast amounts of data, which can be time-consuming and prone to human error. However, with the advent of AI, investigators can now process and analyze this data more efficiently and accurately. For instance, AI algorithms can sift through thousands of documents, images, and videos in a fraction of the time it would take a human investigator, identifying patterns and connections that might otherwise go unnoticed.
Moreover, AI is also proving instrumental in enhancing the accuracy of forensic evidence. In the past, the interpretation of forensic evidence, such as fingerprints or DNA, was largely dependent on the expertise of the investigator. However, AI can now analyze this evidence with a level of precision that far surpasses human capabilities. This not only increases the reliability of the evidence but also reduces the likelihood of wrongful convictions.
In the field of genealogical investigations, AI is similarly making a significant impact. Genealogical research involves tracing family histories and lineages, a task that traditionally required painstaking manual research. However, AI is now being used to automate this process, making it faster and more efficient. AI algorithms can analyze vast databases of historical records, identifying connections and patterns that can help trace a persons ancestry.
Furthermore, AI is also helping to overcome some of the challenges associated with genealogical research. For instance, historical records are often incomplete or inaccurate, making it difficult to trace a persons lineage accurately. However, AI can use predictive modeling to fill in these gaps, providing a more complete picture of a persons ancestry.
In addition, AI is also being used to analyze genetic data in genealogical investigations. This involves using AI algorithms to identify patterns in a persons DNA that can provide clues about their ancestry. This not only enhances the accuracy of genealogical research but also opens up new possibilities for understanding human evolution and migration patterns.
In conclusion, the integration of AI into forensic and genealogical investigations is proving to be a game-changer. By automating data analysis and enhancing the accuracy of evidence and research, AI is not only making these investigations more efficient but also more reliable. As AI continues to evolve, we can expect it to play an even more significant role in these fields, opening up new possibilities for understanding our past and ensuring justice in the present.
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Artificial intelligence isn’t transforming retail accounting, yet – Thomson Reuters
Posted: at 7:24 pm
AI will certainly have an impact on the way that retail accounting work is done, but there is still debate as to the depth and timing of that impact
Artificial intelligence (AI) is all everyone in the business world seems to be talking about today, everything from how it will be used to improve business processes, and which kinds of employees it will replace. And many corporate chief financial officers (CFOs) already are evaluating the potential of AI as a way to increase profits while reducing costs.
Further, a new generation of chatbots is taking over online customer service for businesses, while many firms are using ChatGPT instead of freelance writers to develop content for blogs, websites, email campaigns, and social media posts. Others are using AI to analyze customers online activities to better boost the effectiveness of targeted email marketing campaigns.
AI is also beginning to make baby steps into corporate accounting departments. A new generation of accounts payable and payroll platforms uses rudimentary AI to read scanned invoices, bills, payroll records, 1099 and W-2 forms, and tax notices and then automatically categorize and enter this information into the departments accounting software.
While these uses of AI can help free up time for accountants and bookkeepers who once had to enter this information manually, there is one critical area of accounting where AI is unlikely to make headway soon account reconciliation for retailers and restaurants that generate significant revenue through online sales.
And thats unfortunate, because in this era of razor-thin margins CFOs need to have access to accurate profit & loss information every day. The accountants and bookkeepers they rely on to deliver this information, however, are getting so frustrated by what has become a very labor-intensive and time-consuming process that many are quitting in droves and CFOs are having a very difficult time replacing them.
In an ideal world, an AI-based account-reconciliation platform would automatically download all sales and payment data from every system used by every location, analyze and categorize adjustments, flag exceptions, and prepare summaries for the accountant to review and approve before entering this information into the companys accounting system.
Unfortunately, this isnt going to happen anytime soon. And heres why.
Not only is gaining access to sales data difficult, but an even harder part is making sense of the data. The ability of an AI system to learn is completely dependent on the quality and consistency of the information that is fed into it. AI works best when its trained on structured data that follow predefined rules.
This isnt an issue for payroll records, tax forms, bills, and invoices, which tend to use relatively consistent data structures that make it fairly easy for AI systems to learn and process. Unfortunately, no such consistency exists in the ecommerce world. Each vendor uses siloed sales data formats, with widely variable and often-opaque structures for reporting adjustments. Indeed, some even use their own custom-built platforms with no proper reporting for accountants.
Take state sales taxes, for example. Platforms like Shopify automatically pay taxes on sales made through Instagram and Facebook Marketplace, bt Shopify doesnt clearly label tax adjustments in its transaction records. Instead, its up to the retailers accountant to identify sales taxes and countless other non-annotated adjustments in transaction records, make sure that net sales and deposits match, and resolve exceptions when they dont.
Every time a retailer signs up for a new ecommerce platform or service provider, this creates yet another sales data decoding challenge for accountants and bookkeepers who are already struggling to master existing platforms.
Unfortunately, CFOs cant afford to ignore these problems, because burnout among bookkeepers is becoming a key challenge for retailers.
Further, this is a relatively new phenomenon. Before sales apps like Stripe andShopKeeplaunched in the early 2000s, retail account reconciliation was relatively easy. Most brick-and-mortar retailers generated all of their sales on-site and most accountants and bookkeepers only had to reconcile cash and credit card transactions and download sales reports from a single point-of-sale system.
In recent years, however, everything has changed. Retailers are using upwards of five sales and payment platforms without scrutinizing the quality of the sales reports generated by the systems.As a result of these decisions, many retailers are paying the price in terms of increased attrition among their accountants and bookkeepers.
How bad is the problem? Between 2000 and 2022, more than300,000 accountantsquit their jobs, and today the average turnover rate among corporate accountants is 13.4%.And the outlook for bookkeepers isnt much better. Job growth is expected to decline by 5%through 2030.More problematic is that experienced and knowledgeable veterans are leaving the industry in increasing numbers. As a result, today the average bookkeeper has less thantwo years of experience.
Unfortunately, a universal ChatGPT-style AI solution for retail accounting isnt on the immediate horizon. Not as long as the tax & accounting industry doesnt come together to develop standardized data structure conventions.
However, progress is proceeding on a decentralized scale. Accounting software developers are beginning to move accountants towards data workflows that can convert siloed data-reporting formats into digestible sales data that can eventually train AI systems to process them automatically.
And some of these developers already offer solutions that can automate account reconciliation for retailers using many online sales platforms. For example, automated accounting firms like Bench and Pilot can automatically collect, analyze, and reconcile sales data from systems like Square and Shopify for their accounting clients.
In the meantime, CFOs who arent quite ready to partner with outside accounting automation firms can still support their accountants and bookkeepers by giving them a voice when it comes to choosing or changing sales platforms.
Vendors should be willing to provide samples of downloaded sales reports and transaction records they can review by accountants to assess how much effort it could take to decipher them. And accounting professionals should have the opportunity to meet with members of the vendors development team to ask questions and express concerns about any AI-driven software solution.
CFOs also should be willing to reject any vendorwhose sales feeds would create additional and unnecessary work fortheir accountants and bookkeepers. Or, at the very least, press vendors to explain how they are improving the companys financial reporting and whether the sales data can easily be processed by accounting automation platforms, in case the retailer chooses to partner with one of these firms down the line.
Keep in mind, the easy part is adding new ecommerce platforms to your business. The more challenging aspect is finding and retaining tax & accounting professionals who are willing to work with sub-optimal systems. This is one situation where the value of human capital is far more important than simply making more sales.
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Is artificial intelligence the future of pets? – WISH TV Indianapolis, IN
Posted: at 7:23 pm
INDIANAPOLIS (WISH) Humans have probably heard the phrase dogs are a mans best friend.
Now, it could be AI is a mans best friend.
Artificial intelligence has been a major topic of conversation as it continues to advance and become integrated with everyday life.
For people who grew up in the 1990s, the concept may not be a wild one. After all, we did have Tamagotchi handheld digital pets.
The more recent AI pets are a little more advanced than the electronic pocket pets.
Boston Dynamics and other companies have gone viral several times on social media with videos of their lifelike robot animals. Many of them can run, jump and even follow basic human commands.
China-based company Unittree boasts a robotic companion named the Go1. It walks on all fours as a dog or cat would, and has a following feature so you never have to worry about the robot running off.
According to the company website, there are other options, as well, like the Go2, which comes with a self-charging base for your AI pet.
Dr. Harvey Castro is a Dallas, Texas-based medical professional, and is an expert in AI in health care.
Castro says there are pros and cons to the possibility of artificial intelligence pets.
While robotic pets offer continuous companionship, low maintenance, elimination of allergy exposure, and even mental health support, AI companionship can also be limiting, Castro said in a statement.
Castro added, AI pets cannot replicate the complex and rich experience of caring for a real animal.
He also says they may not be the best for people when it comes to being active. Unlike real pets, A.I. pets dont encourage owners to engage inphysical activity, like walking or playing, Castro said in the statement.
Castro also mentioned the potential risks related to data privacy and dependency on AI pets for companionship, which could lead to the neglect of real-life relationships.
The long-term psychological and emotional effects of having AI pets, especially on children, are yet to be fully understood, Castro said in the statement.
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Artificial Intelligence Takes on the World’s Deadliest Infectious Disease – Good Good Good
Posted: at 7:23 pm
Tuberculosis (TB) is a disease that spreads through the air when people cough, sneeze, or spit, meaning a person only needs to inhale a few germs to become infected.
Its a disease that has plagued human history and continues to kill people in swaths.
The World Health Organization (WHO) calculates that 10 million people across the globe fall ill with TB every year. And, although it is a highly preventable and curable disease, 1.5 million people still die each year because of it making TB the worlds top infectious killer, only falling short of COVID-19.
John Green, an author and philanthropist who often talks about TB on TikTok, puts it into perspective:
If you add up all the people who, in 2022, passed away due to conflict, homicide, malaria, typhoid, and cholera combined, it is still fewer than the number of people who died of Tuberculosis in 2022. What makes that fact crazy, of course, is that Tuberculosis is curable, he said in a video. Tuberculosis is caused by injustice; it is caused by inequitable access to healthcare.
But the WHO aims to end the TB epidemic by 2030 and researchers around the world are using the highest levels of technology to do so.
Take Vietnam, for example, one of 30 countries with the highest burden of TB globally. (An estimated 169,000 people became sick with TB in Vietnam in 2021).
FHI 360, a global organization that mobilizes research and resources to help people have access to healthy lives, and the National TB Control Program of Vietnam are starting at the helm: Accurately diagnosing TB so it can be treated expeditiously.
This effort, which employs the use of artificial intelligence to create a double detection system, works to diagnose and treat TB all while ensuring that patients receive high-quality care without suffering catastrophic costs.
You cant diagnose TB through a self-test, like you can with HIV, Anh Innes, MD, FHI 360s senior technical advisor for Tuberculosis says. You have to have an X-ray. So, to eliminate the disease, we must find the people with TB. Were trying to simplify the diagnosis to make it more point-of-care within the community.
This streamlined diagnosis uses an innovative approach called the Double X Strategy.
FHI 360, along with the U.S. Agency for International Development (USAID) Support to End Tuberculosis project, utilizes the Double X Strategy to combine AI data and direct human professional support to rapidly and accurately detect TB.
The approach uses both X-ray machines and rapid diagnostic machines, called GeneXpert reaching people both in hospitals and in community events with mobile units. Its a win-win-win-win, if we did our calculations correctly.
To detect the disease (or lack thereof), a person at risk of having TB receives a chest X-ray. If the X-ray is abnormal, that person then receives a sputum test with GeneXpert, which can identify M. Tuberculosis DNA.
The test is completed in two hours and results are returned in one to two days. If the test results indicate that the patient has TB, they are started on treatment right away.
In 2020, these partner organizations held 18 community health events in seven Vietnamese provinces, reaching people who live with a TB patient, as well as those with higher TB risks. This led to 52,868 chest X-rays.
Of those scans, 7,968 were determined to be abnormal for TB, and 7,747 people were then tested with GeneXpert, leading to 723 bacteriologically confirmed TB patients.
But where does AI come into play? As experts reach more people through high-volume mobile health screening events, X-ray analyses are aided by AI. Radiologists are able to interpret chest X-rays and quickly compare it with the findings developed by AI software for more accurate results.
In a recent study led by Dr. Frauke Rudolf from Aarhus University, researchers determined that the AI technology was able to match or even outperform professional radiologists in detecting TB.
In an analysis of the X-rays of 498 patients, including 57 diagnosed with TB, the AI software correctly identified 75% of the positive cases and showed an 85.7% accuracy rate in detecting negative results for patients who did not have TB.
The experiment was conducted on mobile phone photographs of chest X-rays, meaning this tech can be applied in underserved areas, where doctors can get a second opinion remotely by sending the scans to the AI.
FHI 360 and USAID use this technology in the Double X Strategy to maximize detection and subsequent treatment.
Using AI with chest X-rays helps ensure that people with TB are identified at all facilities, including lower levels of the health system where staff may have less experience interpreting chest X-rays, an FHI 360 blog post reads.
At community mobile health screening events, where one or two technicians may read hundreds of chest X-rays per day, AI helps avoid decision fatigue and over- or under-selection.
Since 2022, the project has utilized AI to read more than 100,000 X-rays.
These innovations are finding more people in need of TB care and preventative treatment, as well as finding more people who may not necessarily have classic TB symptoms. They have early-stage, subclinical TB, which is an area of emerging research, an FHI 360 press release states. In the past, many early-stage cases would not have been detected without current technology.
The Double X strategy has become Vietnams national TB screening strategy, allowing experts to meet people where they are and create the blueprint to a more holistic approach to battling the worlds deadliest infectious disease.
Developing comprehensive, flexible TB strategies that address all stages of the disease is the way to end TB, the FHI 360 blog post concludes. We must continue updating practices and leveraging new technologies to detect, cure, and prevent this ancient disease that continues to affect communities today.
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Panel of Experts to Discuss the Impact of Artificial Intelligence on … – InsiderNJ
Posted: at 7:23 pm
New Jersey, August 8, 2023 Artificial intelligence and related technologies seem to have promise as groundbreaking and transformative elements in many areas of modern life, including local government. But significant questions remain about these technologies, both on a fundamental level and as they relate to civic life.
These questions and more will be explored during a webinar titled The Impact of Artificial Intelligence and Related Technologies in Local Government on Thursday, August 17 at 12:30 p.m. ET. This free webinar is part of the Corporation for New Jersey Local Medias Community Engagement Series, which promote civic engagement by bringing together experts and journalists to discuss news of local interest and how it impacts our communities. Attendees can register to attend the webinar at: https://us06web.zoom.us/webinar/register/WN_H1grcEuASwegmJ-yVF3zmg.
Webinar panelists include: Senator Andrew Zwicker (D-Hunterdon, Mercer, Middlesex and Somerset), scientist and educator at Princeton Universitys Plasma Physics Laboratory; Professor Marc Pfeiffer, Senior Policy Fellow, Bloustein School of Planning and Public Policy at Rutgers University; Alex Parker-Magyar, editor, Madison Eagle, Florham Park Eagle, and Chatham Courier.
The panel will be moderated by Amanda Richardson, executive director of the Corporation for New Jersey Local Media.
We are pleased to host a webinar focused on an issue that is so timely and of such great importance to our communities, said Richardson. Our webinar series aims to bring light to issues of local and statewide importance by speaking with the people on the ground: reporters, analysts, activists, and politicians.
Generative AI is the newest technology that provides economic benefits for innovators but lacks societal guardrails for users, said Professor Marc Pfeiffer, who also serves on the Governing Board of the Corporation for New Jersey Local Media. We need to learn from the past and then walk (develop safeguards) and chew gum (deploy systems carefully) at the same time.
### Corporation for New Jersey Local Media builds strong communities through journalism and civic engagement. The organization seeks to enhance civic engagement by promoting professional community journalism, fostering public discussion of critical issues, and expanding access to educational programs. Learn more at http://www.newsweneed.org.
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Blending Virtual Reality and Artificial Intelligence Raises Privacy … – Fagen wasanni
Posted: at 7:23 pm
By analyzing the movements of individuals wearing virtual reality (VR) headsets, researchers have demonstrated that a machine learning model can accurately predict personal data such as height, weight, age, marital status, and more. This highlights the potential privacy implications of artificial intelligence (AI) in VR, as personal data can be guessed without users explicitly disclosing it.
In a study conducted at the University of California, Berkeley, researchers were able to identify a specific individual among over 50,000 other VR users with over 94% accuracy after analyzing just 200 seconds of motion data. In another study, researchers accurately determined a persons height, weight, foot size, and country with more than 80% accuracy using data from 1,000 players of the VR game Beat Saber. Additionally, personal information like marital status, employment status, and ethnicity could be identified with more than 70% accuracy.
To analyze the data, the researchers employed a machine learning model that processed uploaded data from VR headsets, such as eye and hand movements. The model could easily identify factors like age, gender, ethnicity, and country. More nuanced information, including income level, disability status, health status, and even political preference, could also be inferred.
VR headsets capture data that traditional websites or apps cannot, such as gaze, body language, body proportions, and facial expressions. This combination of data intensifies privacy concerns and raises additional issues beyond those faced by conventional platforms.
Meta Platforms Inc., a major VR headset manufacturer, uses machine learning to fill in gaps in its knowledge of users, particularly since Apple limited the amount of data that can be tracked on its iPhones. VR headsets, therefore, represent an opportunity for Meta to collect more data to improve ad targeting and revenue generation through advertising.
Protecting privacy in VR headsets is challenging due to the necessity of collecting data like eye and hand movements. Encryption and limiting stored data are potential solutions, but companies producing VR headsets have incentives to collect information for marketing purposes.
Privacy controls and consumer awareness are currently inadequate in the VR space. The capabilities of AI, coupled with limited understanding of the technology among users and regulators, pose significant challenges for individuals to protect their privacy effectively.
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Solving IT Challenges with Artificial Intelligence: A Comprehensive … – Fagen wasanni
Posted: at 7:23 pm
Overcoming IT Hurdles: A Comprehensive Guide to Solving IT Challenges with Artificial Intelligence
The world of information technology (IT) is constantly evolving, bringing forth new challenges that need innovative solutions. One such solution that has gained significant traction in recent years is Artificial Intelligence (AI). By leveraging AI, businesses can overcome a myriad of IT hurdles, from data management to cybersecurity threats, and improve their overall operational efficiency.
The first major challenge that AI can help address is data management. In the digital age, businesses generate and collect vast amounts of data. Managing this data, ensuring its accuracy, and extracting meaningful insights from it can be a daunting task. However, AI, with its machine learning capabilities, can automate data management processes, analyze complex data sets, and provide actionable insights. This not only saves time and resources but also helps businesses make data-driven decisions.
Next, AI can significantly enhance cybersecurity measures. With cyber threats becoming increasingly sophisticated, traditional security measures are often insufficient. AI can help by constantly learning from these threats and adapting security measures accordingly. For instance, AI can identify patterns in cyber-attacks, predict potential threats, and implement preventive measures, thereby providing a robust defense against cyber threats.
Moreover, AI can streamline IT operations by automating routine tasks. IT departments often spend a significant amount of time on mundane tasks such as system maintenance and troubleshooting. AI can automate these tasks, freeing up IT professionals to focus on more strategic initiatives. Additionally, AI can predict IT system failures and take corrective action before the issue escalates, thereby minimizing downtime and improving system reliability.
Another area where AI can make a significant impact is customer service. With AI-powered chatbots, businesses can provide 24/7 customer support, resolve queries promptly, and improve customer satisfaction. These chatbots can learn from past interactions, thereby enhancing their ability to resolve customer queries over time.
Furthermore, AI can help in resource allocation. By analyzing past data, AI can predict future resource requirements and help businesses plan accordingly. This can result in cost savings and improved efficiency. For instance, AI can predict when a business might experience a surge in website traffic and allocate resources accordingly to prevent website downtime.
Finally, AI can aid in decision-making. By analyzing data and providing insights, AI can help businesses make informed decisions. Whether its deciding on the best marketing strategy or identifying potential areas of investment, AI can provide valuable input that can drive business growth.
In conclusion, AI presents a comprehensive solution to various IT challenges. By automating routine tasks, enhancing cybersecurity, improving customer service, aiding in resource allocation, and facilitating decision-making, AI can significantly improve business operations. However, its important to note that the successful implementation of AI requires a strategic approach. Businesses need to clearly define their objectives, invest in the right AI tools, and train their staff to effectively use these tools. With the right approach, businesses can harness the power of AI to overcome IT hurdles and drive growth.
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The Impact of Artificial Intelligence in the Retail Sector – Fagen wasanni
Posted: at 7:23 pm
Artificial intelligence (AI) has been recognized as the most disruptive technology since Q3 2021, and this holds true across various industries, including the retail sector.
Retailers are increasingly investing in AI with the goal of boosting sales, stabilizing supply chains, improving planning processes, and enhancing customer relations.
One area where AI is making a significant impact is in supply chain forecasting. Through machine learning, retailers can accurately predict demand by considering hundreds of influencing factors. This enables better planning across merchandising, supply chains, and operations, providing visibility into future demand for every product in every store and channel.
Retailers such as One Stop have already implemented AI forecasting solutions and have reported positive results. After just four months of using an AI forecasting solution, One Stop saw a 5% increase in store availability across their entire range, leading to a significant increase in sales.
AI is also helping retailers cut operational costs through the use of chatbots. Automated cashier-free stores, like Amazon Go, have been successful in reducing queues and operational expenses. AI-powered chatbots are being adopted by brands like Burberry to enhance customer service, improve searchability, and provide personalized product suggestions.
Pricing and clearance optimization software is another area where AI is transforming the retail sector. These solutions automate markdowns and clearance processes, eliminating manual tasks and reducing the risk of excess stock. Retailers can identify products for clearance and set optimized discounts based on desired outcomes. This helps improve margins and inventory turnover.
The use of AI in the retail sector is diverse and constantly evolving. Companies that embrace AI technology will position themselves as industry leaders, while those who overlook its potential may struggle to keep up with the competition. The adoption of AI will play a crucial role in determining the winners and losers in the retail sector of tomorrow.
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AI in Education – EducationNext
Posted: August 8, 2023 at 10:56 am
In Neal Stephensons 1995 science fiction novel, The Diamond Age, readers meet Nell, a young girl who comes into possession of a highly advanced book, The Young Ladys Illustrated Primer. The book is not the usual static collection of texts and images but a deeply immersive tool that can converse with the reader, answer questions, and personalize its content, all in service of educating and motivating a young girl to be a strong, independent individual.
Such a device, even after the introduction of the Internet and tablet computers, has remained in the realm of science fictionuntil now. Artificial intelligence, or AI, took a giant leap forward with the introduction in November 2022 of ChatGPT, an AI technology capable of producing remarkably creative responses and sophisticated analysis through human-like dialogue. It has triggered a wave of innovation, some of which suggests we might be on the brink of an era of interactive, super-intelligent tools not unlike the book Stephenson dreamed up for Nell.
Sundar Pichai, Googles CEO, calls artificial intelligence more profound than fire or electricity or anything we have done in the past. Reid Hoffman, the founder of LinkedIn and current partner at Greylock Partners, says, The power to make positive change in the world is about to get the biggest boost its ever had. And Bill Gates has said that this new wave of AI is as fundamental as the creation of the microprocessor, the personal computer, the Internet, and the mobile phone.
Over the last year, developers have released a dizzying array of AI tools that can generate text, images, music, and video with no need for complicated coding but simply in response to instructions given in natural language. These technologies are rapidly improving, and developers are introducing capabilities that would have been considered science fiction just a few years ago. AI is also raising pressing ethical questions around bias, appropriate use, and plagiarism.
In the realm of education, this technology will influence how students learn, how teachers work, and ultimately how we structure our education system. Some educators and leaders look forward to these changes with great enthusiasm. Sal Kahn, founder of Khan Academy, went so far as to say in a TED talk that AI has the potential to effect probably the biggest positive transformation that education has ever seen. But others warn that AI will enable the spread of misinformation, facilitate cheating in school and college, kill whatever vestiges of individual privacy remain, and cause massive job loss. The challenge is to harness the positive potential while avoiding or mitigating the harm.
What Is Generative AI?
Artificial intelligence is a branch of computer science that focuses on creating software capable of mimicking behaviors and processes we would consider intelligent if exhibited by humans, including reasoning, learning, problem-solving, and exercising creativity. AI systems can be applied to an extensive range of tasks, including language translation, image recognition, navigating autonomous vehicles, detecting and treating cancer, and, in the case of generative AI, producing content and knowledge rather than simply searching for and retrieving it.
Foundation models in generative AI are systems trained on a large dataset to learn a broad base of knowledge that can then be adapted to a range of different, more specific purposes. This learning method is self-supervised, meaning the model learns by finding patterns and relationships in the data it is trained on.
Large Language Models (LLMs) are foundation models that have been trained on a vast amount of text data. For example, the training data for OpenAIs GPT model consisted of web content, books, Wikipedia articles, news articles, social media posts, code snippets, and more. OpenAIs GPT-3 models underwent training on a staggering 300 billion tokens or word pieces, using more than 175 billion parameters to shape the models behaviornearly 100 times more data than the companys GPT-2 model had.
By doing this analysis across billions of sentences, LLM models develop a statistical understanding of language: how words and phrases are usually combined, what topics are typically discussed together, and what tone or style is appropriate in different contexts. That allows it to generate human-like text and perform a wide range of tasks, such as writing articles, answering questions, or analyzing unstructured data.
LLMs include OpenAIs GPT-4, Googles PaLM, and Metas LLaMA. These LLMs serve as foundations for AI applications. ChatGPT is built on GPT-3.5 and GPT-4, while Bard uses Googles Pathways Language Model 2 (PaLM 2) as its foundation.
Some of the best-known applications are:
ChatGPT 3.5. The free version of ChatGPT released by OpenAI in November 2022. It was trained on data only up to 2021, and while it is very fast, it is prone to inaccuracies.
ChatGPT 4.0. The newest version of ChatGPT, which is more powerful and accurate than ChatGPT 3.5 but also slower, and it requires a paid account. It also has extended capabilities through plug-ins that give it the ability to interface with content from websites, perform more sophisticated mathematical functions, and access other services. A new Code Interpreter feature gives ChatGPT the ability to analyze data, create charts, solve math problems, edit files, and even develop hypotheses to explain data trends.
Microsoft Bing Chat. An iteration of Microsofts Bing search engine that is enhanced with OpenAIs ChatGPT technology. It can browse websites and offers source citations with its results.
Google Bard. Googles AI generates text, translates languages, writes different kinds of creative content, and writes and debugs code in more than 20 different programming languages. The tone and style of Bards replies can be finetuned to be simple, long, short, professional, or casual. Bard also leverages Google Lens to analyze images uploaded with prompts.
Anthropic Claude 2. A chatbot that can generate text, summarize content, and perform other tasks, Claude 2 can analyze texts of roughly 75,000 wordsabout the length of The Great Gatsbyand generate responses of more than 3,000 words. The model was built using a set of principles that serve as a sort of constitution for AI systems, with the aim of making them more helpful, honest, and harmless.
These AI systems have been improving at a remarkable pace, including in how well they perform on assessments of human knowledge. OpenAIs GPT-3.5, which was released in March 2022, only managed to score in the 10th percentile on the bar exam, but GPT-4.0, introduced a year later, made a significant leap, scoring in the 90th percentile. What makes these feats especially impressive is that OpenAI did not specifically train the system to take these exams; the AI was able to come up with the correct answers on its own. Similarly, Googles medical AI model substantially improved its performance on a U.S. Medical Licensing Examination practice test, with its accuracy rate jumping to 85 percent in March 2021 from 33 percent in December 2020.
These two examples prompt one to ask: if AI continues to improve so rapidly, what will these systems be able to achieve in the next few years? Whats more, new studies challenge the assumption that AI-generated responses are stale or sterile. In the case of Googles AI model, physicians preferred the AIs long-form answers to those written by their fellow doctors, and nonmedical study participants rated the AI answers as more helpful. Another study found that participants preferred a medical chatbots responses over those of a physician and rated them significantly higher, not just for quality but also for empathy. What will happen when empathetic AI is used in education?
Other studies have looked at the reasoning capabilities of these models. Microsoft researchers suggest that newer systems exhibit more general intelligence than previous AI models and are coming strikingly close to human-level performance. While some observers question those conclusions, the AI systems display an increasing ability to generate coherent and contextually appropriate responses, make connections between different pieces of information, and engage in reasoning processes such as inference, deduction, and analogy.
Despite their prodigious capabilities, these systems are not without flaws. At times, they churn out information that might sound convincing but is irrelevant, illogical, or entirely falsean anomaly known as hallucination. The execution of certain mathematical operations presents another area of difficulty for AI. And while these systems can generate well-crafted and realistic text, understanding why the model made specific decisions or predictions can be challenging.
The Importance of Well-Designed Prompts
Using generative AI systems such as ChatGPT, Bard, and Claude 2 is relatively simple. One has only to type in a request or a task (called a prompt), and the AI generates a response. Properly constructed prompts are essential for getting useful results from generative AI tools. You can ask generative AI to analyze text, find patterns in data, compare opposing arguments, and summarize an article in different ways (see sidebar for examples of AI prompts).
One challenge is that, after using search engines for years, people have been preconditioned to phrase questions in a certain way. A search engine is something like a helpful librarian who takes a specific question and points you to the most relevant sources for possible answers. The search engine (or librarian) doesnt create anything new but efficiently retrieves whats already there.
Generative AI is more akin to a competent intern. You give a generative AI tool instructions through prompts, as you would to an intern, asking it to complete a task and produce a product. The AI interprets your instructions, thinks about the best way to carry them out, and produces something original or performs a task to fulfill your directive. The results arent pre-made or stored somewheretheyre produced on the fly, based on the information the intern (generative AI) has been trained on. The output often depends on the precision and clarity of the instructions (prompts) you provide. A vague or poorly defined prompt might lead the AI to produce less relevant results. The more context and direction you give it, the better the result will be. Whats more, the capabilities of these AI systems are being enhanced through the introduction of versatile plug-ins that equip them to browse websites, analyze data files, or access other services. Think of this as giving your intern access to a group of experts to help accomplish your tasks.
One strategy in using a generative AI tool is first to tell it what kind of expert or persona you want it to be. Ask it to be an expert management consultant, a skilled teacher, a writing tutor, or a copy editor, and then give it a task.
Prompts can also be constructed to get these AI systems to perform complex and multi-step operations. For example, lets say a teacher wants to create an adaptive tutoring programfor any subject, any grade, in any languagethat customizes the examples for students based on their interests. She wants each lesson to culminate in a short-response or multiple-choice quiz. If the student answers the questions correctly, the AI tutor should move on to the next lesson. If the student responds incorrectly, the AI should explain the concept again, but using simpler language.
Previously, designing this kind of interactive system would have required a relatively sophisticated and expensive software program. With ChatGPT, however, just giving those instructions in a prompt delivers a serviceable tutoring system. It isnt perfect, but remember that it was built virtually for free, with just a few lines of English language as a command. And nothing in the education market today has the capability to generate almost limitless examples to connect the lesson concept to students interests.
Chained prompts can also help focus AI systems. For example, an educator can prompt a generative AI system first to read a practice guide from the What Works Clearinghouse and summarize its recommendations. Then, in a follow-up prompt, the teacher can ask the AI to develop a set of classroom activities based on what it just read. By curating the source material and using the right prompts, the educator can anchor the generated responses in evidence and high-quality research.
However, much like fledgling interns learning the ropes in a new environment, AI does commit occasional errors. Such fallibility, while inevitable, underlines the critical importance of maintaining rigorous oversight of AIs output. Monitoring not only acts as a crucial checkpoint for accuracy but also becomes a vital source of real-time feedback for the system. Its through this iterative refinement process that an AI system, over time, can significantly minimize its error rate and increase its efficacy.
Uses of AI in Education
In May 2023, the U.S. Department of Education released a report titled Artificial Intelligence and the Future of Teaching and Learning: Insights and Recommendations. The department had conducted listening sessions in 2022 with more than 700 people, including educators and parents, to gauge their views on AI. The report noted that constituents believe that action is required now in order to get ahead of the expected increase of AI in education technologyand they want to roll up their sleeves and start working together. People expressed anxiety about future potential risks with AI but also felt that AI may enable achieving educational priorities in better ways, at scale, and with lower costs.
AI could serveor is already servingin several teaching-and-learning roles:
Instructional assistants. AIs ability to conduct human-like conversations opens up possibilities for adaptive tutoring or instructional assistants that can help explain difficult concepts to students. AI-based feedback systems can offer constructive critiques on student writing, which can help students fine-tune their writing skills. Some research also suggests certain kinds of prompts can help children generate more fruitful questions about learning. AI models might also support customized learning for students with disabilities and provide translation for English language learners.
Teaching assistants. AI might tackle some of the administrative tasks that keep teachers from investing more time with their peers or students. Early uses include automated routine tasks such as drafting lesson plans, creating differentiated materials, designing worksheets, developing quizzes, and exploring ways of explaining complicated academic materials. AI can also provide educators with recommendations to meet student needs and help teachers reflect, plan, and improve their practice.
Parent assistants. Parents can use AI to generate letters requesting individualized education plan (IEP) services or to ask that a child be evaluated for gifted and talented programs. For parents choosing a school for their child, AI could serve as an administrative assistant, mapping out school options within driving distance of home, generating application timelines, compiling contact information, and the like. Generative AI can even create bedtime stories with evolving plots tailored to a childs interests.
Administrator assistants. Using generative AI, school administrators can draft various communications, including materials for parents, newsletters, and other community-engagement documents. AI systems can also help with the difficult tasks of organizing class or bus schedules, and they can analyze complex data to identify patterns or needs. ChatGPT can perform sophisticated sentiment analysis that could be useful for measuring school-climate and other survey data.
Though the potential is great, most teachers have yet to use these tools. A Morning Consult and EdChoice poll found that while 60 percent say theyve heard about ChatGPT, only 14 percent have used it in their free time, and just 13 percent have used it at school. Its likely that most teachers and students will engage with generative AI not through the platforms themselves but rather through AI capabilities embedded in software. Instructional providers such as Khan Academy, Varsity Tutors, and DuoLingo are experimenting with GPT-4-powered tutors that are trained on datasets specific to these organizations to provide individualized learning support that has additional guardrails to help protect students and enhance the experience for teachers.
Googles Project Tailwind is experimenting with an AI notebook that can analyze student notes and then develop study questions or provide tutoring support through a chat interface. These features could soon be available on Google Classroom, potentially reaching over half of all U.S. classrooms. Brisk Teaching is one of the first companies to build a portfolio of AI services designed specifically for teachersdifferentiating content, drafting lesson plans, providing student feedback, and serving as an AI assistant to streamline workflow among different apps and tools.
Providers of curriculum and instruction materials might also include AI assistants for instant help and tutoring tailored to the companies products. One example is the edX Xpert, a ChatGPT-based learning assistant on the edX platform. It offers immediate, customized academic and customer support for online learners worldwide.
Regardless of the ways AI is used in classrooms, the fundamental task of policymakers and education leaders is to ensure that the technology is serving sound instructional practice. As Vicki Phillips, CEO of the National Center on Education and the Economy, wrote, We should not only think about how technology can assist teachers and learners in improving what theyre doing now, but what it means for ensuring that new ways of teaching and learning flourish alongside the applications of AI.
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The Role of Artificial Intelligence in the Future of Media – Fagen wasanni
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There has been some confusion and concern among people about the role of artificial intelligence (AI) in our lives. However, AI is simply a technology that can perform tasks requiring human intelligence. It learns from data and improves its performance over time. AI has the potential to drive nearly 45% of the economy by 2023.
AI can be categorized into three types: Narrow AI, General AI, and Super AI. Narrow AI is designed for specific tasks, while General AI can perform any intellectual task that a human can do, although it doesnt exist yet. Super AI is purely theoretical and surpasses human intelligence in every aspect.
For media companies, AI applications like content personalization, automated content generation, sentiment analysis, and audience targeting can greatly benefit content delivery and audience engagement. AI can analyze customer data for targeted marketing campaigns, create personalized content, predict customer behavior, analyze visual content, and assist in social media management.
Companies can transition to AI by identifying pain points, collecting and preparing relevant data, starting with narrow applications, collaborating with AI experts, and forming a task force to integrate AI across the organization. AI can automate repetitive tasks, enhance decision-making, and free up human resources for more strategic work.
However, it is important for brands to maintain authenticity and embrace diversity while using AI for marketing. AI algorithms are only as unbiased as the data they are trained on, so brands should use diverse data and establish ethical guidelines to mitigate biases. Human creativity and understanding are irreplaceable, and brands should emphasize the importance of human-AI collaboration.
Overall, AI has the potential to revolutionize the media industry by improving customer experiences, optimizing operations, and delivering relevant content. It is crucial for companies to understand and leverage the power of AI to stay competitive in the evolving digital landscape.
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The Role of Artificial Intelligence in the Future of Media - Fagen wasanni
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