AI tools for various tasks

Natural Language Processing has advanced rapidly, supporting the creation of intelligent systems that can understand language better and more clearly than ever. ChatGPT, PaLM, DALL-E are some of the large language models that are constantly improving and achieving higher performance. These models mimic humans and help with tasks such as textual content creation, text summarization, question answering, code completion, video surveillance and more. LLMs are trained on huge amounts of data and have shown great results in almost every domain. Generative AI tools spread on many types of tasks, from being a conversation partner to creating videos based on a (short) text description. Some of the best AI tools for various tasks are:

• Text: Jasper, ChatGPT, Surfer, Grammarly, Wordtune, Hemingway
• Image: DALL·E 2, MidJourney, Stable Diffusion, neural.love, Nvidia Canvas
• Video: Descript, Wondershare Filmora, Runway, Fliki, Synthesia
• Other: Mem (note-taking), Beautiful.ai (slide decks), Otter (transcription), Looka Logo Maker (logo creation), Wix ADI (website building) and so on.

As AI technology continues to evolve, we can expect even more sophisticated tools and applications, ultimately reshaping the way we interact with and interpret data in the digital age. They are based on more and more sophisticated technologies:

Text Analysis

1. Natural Language Processing (NLP): NLP-powered AI tools like GPT-3 have gained immense popularity for their ability to generate human-like text, answer questions, and translate languages. They find applications in content creation, chatbots, sentiment analysis, and language translation.
2. Text Summarization: Tools such as BertSum and Gensim's TextRank use AI algorithms to summarize lengthy texts, making it easier to extract key information from documents and articles. They are invaluable for research, news, and content curation.
3. Sentiment Analysis: Tools like VADER and TextBlob utilize AI to analyse and categorize text based on sentiments, such as positive, negative, or neutral. These tools are widely used for social media monitoring, customer feedback analysis, and brand perception management.

Image Processing

1. Computer Vision: AI tools like OpenCV and TensorFlow offer robust computer vision capabilities, enabling tasks such as object detection, image classification, and facial recognition. These tools find applications in autonomous vehicles, medical image analysis, and security systems.
2. Image Generation: Generative Adversarial Networks (GANs) and StyleGAN have revolutionized image generation. They can create highly realistic images, art, and design elements, transforming the creative industries.
3. Image Enhancement: AI-based tools like DeOldify and Adobe's Sensei utilize deep learning to enhance and restore old or low-quality images. They are valuable in preserving historical photographs and improving image quality for various applications.

Video Analysis

1. Video Summarization: AI tools like VideoAI and IBM Watson Video Analyzer use machine learning algorithms to summarize video content, making it easier to extract key information and trends from lengthy videos. This is crucial for security surveillance, video indexing, and content moderation.
2. Video Object Tracking: AI-powered object tracking tools, such as DeepSORT, enable real-time tracking of objects within videos, facilitating applications like autonomous drones, sports analytics, and video production.
3. Emotion Recognition: Tools like Affectiva and Amazon Rekognition Video can recognize emotions in video content, allowing for sentiment analysis in marketing research, user experience testing, and mental health applications.

ChatGPT, Bing Chat, Claude 2

For conversations or text generation, the best-known application is ChatGPT, launched by the company OpenAI (https://chat.openai.com/chat – account required), with a slightly more advanced version embedded in Bing search engine ( https://www.bing.com/search?q=Bing+AI&showconv=1 – with free access, but only through Edge browser). In a comparison with ChatGPT, Bing Chat (1) can be used without an account, (2) uses ChatGPT4, (3) you can use images along with text instructions, (4) creates images, (5) summarises web pages, (6) finds a movie or TV show and open it in the app you are choosing/ where you have a subscription.

Recently released Claude 2 (https://claude.ai – account required), a generative AI chatbot developed by Anthropic, also has some benefits over the free version of ChatGPT: (1) read, analyse, and summarize uploaded files, (2) process more words than ChatGPT, (3) provide information after 2021, (4) access links and summarize their contents.

For longer texts, such as syntheses, reports and essays on a specific topic, Playground OpenAI (an OpenAI product) or Playground AI21Studio (created by AI21) can also be used. Both require the creation of a user account and allow control of the length of the generated text by setting a maximum number of characters (maximum length). They also allow selection of a language model as needed from several predefined options. Some examples of texts developed with the Playground tool on the topic of education can be found here: digital-pedagogy.eu/ariadna-experiment-the-role-of-artificial-intelligence-in-education-sciences/#signal (December 2022).

Images and videos

To generate images, you can use, among many others, Bing Image Creator (https://www.bing.com/create), DALL-E (https://openai.com/product/dall-e-2 – account required) and Fotor (https://www.fotor.com/features/ai-image-generator/ ).

AI photo apps are very popular. Many tools to generate and edit photos are now available for students and teachers for free or as freemium/ free trial: Lensa AI, Voi, Remini, Pixelup, Fotor, Wonder, FacePlay, Aiby, FaceApp, Gradient, Dawn AI, Facetune, Prequel, Voilà AI Artist, New Profile Pic Avatar Maker, Meitu and so on. They can help to edit photos (remove persons and objects, change backgrounds), create avatars from pictures, turn photos into cartoons, generate similar photos etc.

As regards the text-to-video AI generators, short tutorials for 5 AI text-to-video tools are presented here: youtube.com/watch?v=8HpQgEEhbC4. The AI tools are:

1. Lucas: https://www.idomoo.com/ai-video-creator-lp/
2. Pictory: https://pictory.ai/
3. Wave Video: https://wave.video/
4. Lumen5: https://lumen5.com/
5. inVideo: https://invideo.io/

Other types of AI tools to try

PinwheelGPT (https://www.pinwheel.com/gpt - app installation needed – free for up to 20 questions a month) have kid-safe guardrails, to make sure the interaction is appropriate for kids 7-12. A history of conversations is available for parents, even if the kids deleted the questions.

Tome (https://tome.app – freemium ) creates captivating visuals from any input.

Whisper Memos (https://whispermemos.com – free to start – available for iOS – app installation needed) turns your voice into transcripts. A voice memo recorder that transcribe what you say and emails it to you.

Eleven Labs (https://elevenlabs.io – free to start) is a text to speech app. It can also clone your voice (feature requiring a paid subscription starting at $1).

Copyright

A legitimate question arising when using AI tools in various activities is: The output is mine? Should I mention the AI tool somewhere/ somehow?

In other words, under what conditions do works made with the contribution of AI benefit from copyright protection?

For now, there is no clear answer to this question. Specifically, there are still some steps to be taken before the contribution of artificial intelligence is introduced into the legislation. In any case, professional ethics require mentioning the fact that a work was done with the help of AI.

In the United States, the institution that administers the national copyright system and regulates most aspects of intellectual property is the U.S. Copyright Office (USCO). For a work to be eligible for copyright protection, the answer to each of the following questions must be yes (USCO, 2017, Art. 302, pg. 48):

• Is the work eligible for copyright protection in the United States?
• Has the work been fixed in a tangible medium of expression?
• Was the work created by a human author?
• Does the work constitute copyrightable subject matter?
• Is the work sufficiently original? (Was the work independently created? Does the work possess at least a minimal degree of creativity?)

If the answer to all these questions is ”yes”, then the work can be registered for protection. In other words, only if it meets these 5 conditions the product can be the subject of an intellectual property dispute. Article 306 stipulates the need for the author to be a human being, also referring to a text from 1879, which states that copyright law protects only ”the fruits of intellectual labor” that ”are founded in the creative powers of the mind”. The Copyright Office refuses to consider any appeal if it is determined that the product is not created by a human being.

But what if, in a collaborative intellectual effort, one of the ”creative minds” is artificial?

More recently, the need to revise these regulations on the protection of intellectual property has led to the initiation of broad debates, both in the United States, starting in 2019, and in Europe, to respond to the challenges brought by artificial intelligence.

The outcome of intellectual property debates is important because it regulates behaviour and how to report on it – it clearly establishes the conditions under which intellectual property is infringed and provides support for fraud prevention and countermeasures. Moreover (because it seems to be needed), this debate reinforces and updates some ethical principles, outlines and supports a moral stance, recalls and clarifies the essence of the human spirit, in parallel with a more or less intelligent computer program.

The impact of AI concerns works of different nature, from texts of various types, fiction, scientific articles, computer programs, to films, images, procedures, and solutions to problems very diverse in their nature, prototypes, and sketches of innovative products. The current debate has deeper implications. It may involve a repositioning, a different perspective on how we relate to various situations or to the (use of) simpler or more complex tools. For example, if, in order to create an iron art object, someone uses a filter and protection tool (a welding mask), should they specify this explicitly, in a visible place, next to their name labelling their position as the author of the work? Similarly, to what extent does a selection of responses to a series of well-formulated and logically structured questions, along with my interpretation, constitute my own work? And to what extent does it constitute the work of the person who answered the questions (in this case, an AI program)? In a (qualitative) research of 50 years ago, was every respondent credited as an author? Of course not. Should they be credited as the author? They probably should. But if I use the ideas from 100 articles on a certain topic to develop another article, reformulating, synthesizing, arranging in a certain logic – is this my work, original, protected by copyright law? If a computer application does this at my direction, who is the author(s)?

In the situation where we use AI to support the development of intellectual products, crediting the AI tool cannot give it the authorship, but rather consists of a note acknowledging its contribution, the author being the person who used the application/tool / artificial intelligence program and who is accountable for the work.

Remember!

Text, images or sounds generated by an AI tool cannot be attributed to it.

The examples in the compendium of the United States Copyright Office seem hilarious, but they are needed to understand and manage various current situations that use artificial intelligence. The following types of works cannot constitute an eligible work to be protected (USCO, pg. 63, Art. 313.2 et seq.):

• A photo taken by a monkey.
• A mural painted by an elephant.
• A piece of wood shaped by the ocean.
• A song naming the Holy Spirit as the author of the work.
• Reducing or increasing the size of a pre-existing work.
• Converting a work from analog to digital, such as transferring a motion picture from VHS to DVD.
• Transposing a song from B major to C major
• Medical imaging produced by X-rays, ultrasounds, magnetic resonance imaging or other diagnostic equipment
• A product based on a mechanical weaving process that randomly produces irregular shapes in the fabric without any discernible pattern.

We see many similarities with how we can interpret the contribution of ChatGPT or any artificial intelligence program nowadays to the development of an intellectual product. A current question is: Is there a case where a machine could or should actually own the copyright for something that it created on its own without significant human involvement? (Cochetti, 2023). More discussion and research are needed at the intersection of AI and intellectual property to redraw the scope and effects of copyright (UNESCO, 2022, pg. 33, Art. 99).

Many of the AI-generated texts, while appearing coherent and semantically plausible, are actually similar to the last counterexample on the U.S. Copyright Office’s 2017 list, ”a product based on a mechanical weaving process that produces random irregular shapes in the fabric without any discernible pattern”, with the difference that the AI is now trained to make the generated item appear to have a pattern.

Reflect on consequences!

Artificial intelligence is not ”concerned” about truth or originality, but with constructing a plausible product, generating the most likely sequel for each sequence of text, image or sound, using as a benchmark a database of similar digital products.

Image generated with Fotor/ 16:9, Photography 1, instruction: ”Digital product, a communist environment 9 centuries B.C., AI art, photographic style” (Sept. 2023)

Image generated with Fotor/ 16:9, Photography 1, instruction: ”Digital product, several people in a communist environment 9 centuries B.C., AI art, photographic style” (Sept. 2023)

Pending general and specific legislation on the role and contribution of AI in each case, it seems important to have this starting point – some ideas to reflect on, alongside a suite of recommendations and examples of current practice.

 Does content generated with artificial intelligence applications have intellectual property restrictions?

Content generated with artificial intelligence applications does not (for now?) have intellectual property restrictions – it can be used freely, for any legal means, including commercial use. Moreover, the obtained content should be associated with the person who made the request, if they made it on their own behalf, or the company, if they have an institutional account or made the request for professional purposes. We are already talking about articles and even books co-authored with artificial intelligence. The policy of OpenAI, the company that owns ChatGPT and many other AI tools, states:

Creators who wish to publish their first-party written content (e.g., a book, compendium of short stories) created in part with the OpenAI API are permitted to do so under the following conditions:

• The published content is attributed to your name or company.
• The role of AI in formulating the content is clearly disclosed in a way that no reader could possibly miss, and that a typical reader would find sufficiently easy to understand.
• Topics of the content do not violate OpenAI’s Content Policy or Terms of Use, e.g., are not related to adult content, spam, hateful content, content that incites violence, or other uses that may cause social harm.
• We kindly ask that you refrain from sharing outputs that may offend others.
  (Source: https://openai.com/policies/sharing-publication-policy, 19 Jan. 2023)

How to cite ChatGPT and Bing Chat?

There are two types of customs to indicate the addition of artificial intelligence, one is for in-text citation (just as one cites an out-of-print source) as well as addition to the bibliography, and the other is for the addition of visible informational text, usually placed at the end of the article. It is ideal to use both variants.

Example of in-text citation using the APA standard:

(ChatGPT, personal communication, April 9, 2023) or simply: (OpenAI, 2023)

Example of a bibliographic reference using the APA standard:

OpenAI. (2023). ChatGPT (Apr. 9 version) [Large language model]. https://chat.openai.com/chat

Example of an in-text reference/citation using MLA format:

(OpenAI. ChatGPT. Chat.openai.com/. Accessed Apr. 9, 2023)

The information text suggested by OpenAI to add to content generated with Chat GPT is: The author generated this text in part with GPT-3 [or later versions], OpenAI’s large-scale language-generation model. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.

Microsoft’s intelligent search assistant Bing Chat is available for free in the Edge browser, since March. It provides personalized answers to various questions, processing the relevant content obtained from various sites, developing texts in most cases original, new.

The content generated by Chat integrated into Bing is basically your property. The terms and conditions of use of Microsoft services, including Bing Chat, state (as of April 2023):

Art. 8. Ownership of content. Microsoft does not claim ownership of Captions, Prompts, Creations or any other content you provide, post, input, or submit to, or receive from, the Online Services (including feedback and suggestions).

However, we recommend you to quote and credit the source for content taken from Bing Chat.

Example of simple in-text reference/ bibliographic citation, using APA format:

(Bing Chat, personal communication, April 9, 2023)

Example of a simple in-text reference/ bibliographic citation using MLA format:

(Microsoft. Bing Chat. https://www.bing.com/chat. Accessed 9 Apr. 2023)

The informational text to be added at the end of the material can be similar, since it is anyway also about Chat GPT: The author generated this text in part with Bing Chat/ GPT-3 [or later versions]. Upon generating draft language, the author reviewed, edited, and revised the language to their own liking and takes ultimate responsibility for the content of this publication.

It should be noted that, unlike ChatGPT on the OpenAI platform, searching and generating new answers through Bing Chat also provides a „bibliography” under the title „Learn more”, that includes the most important sources contributing to the development of the answer provided. We recommend that you go through them and, where appropriate, cite them separately – both in the text and in the bibliography, using the APA standard specific to that type of work.

How to reference images generated with AI programs?

In the case of images, the program used can be specified at the end of the material that contains them:

The images in this material were generated with Fotor (fotor.com).

Or you can insert a note next to each image:

Image generated with Fotor AI Face Generator (https://www.fotor.com/features/ai-face-generator/, Apr 9, 2023)

Or, more specifically:

This image was generated with Fotor AI Image Generator (https://www.fotor.com/features/ai-image-generator/, on April 9, 2023, with the request: „Little elephant talking with a boy on the Moon” )

Or

„Little elephant talking with a boy on the Moon” – image generated with Bing Image Creator (https://www.bing.com/create , 9 April 2023)

In scientific works, a serial number and title must be added before the image, as well as a note after the image (if necessary).

Figure 2. A boy talking to an elephant on the moon