With the rise of artificial intelligence and machine learning, there has been a surge in the generation of images and other content. Unfortunately, with this increase comes the issue of plagiarism. Plagiarism, or the unauthorized use of someone else’s work and claiming it as one’s own, is an ever-growing problem in the digital age. But what about when it comes to AI-generated images? Is it possible for a machine to plagiarize? And should AI-generated images or prompts used to produce them be protected under copyright law?
On one hand, it can be argued that AI-generated images are not subject to plagiarism. After all, machines can only generate images based on the data that is given to them. It’s a process of learning and understanding, rather than creating something completely new. As such, it can be argued that AI-generated images are not plagiarizing, but rather using existing data to create something new.
On the other hand, if an AI is given a dataset of images and then uses that data to create a “new” image, it is still taking someone else’s work and claiming it as one’s own and can thus be considered plagiarism, even if the AI is not actually creating something original.
When it comes to protecting AI-generated images under copyright law, on one side, it can be argued that AI-generated images should be protected because they are the product of creative effort and should therefore be eligible for copyright protection. On the other hand, there is an argument that AI-generated images should not be protected because they do not involve any human creativity and are therefore not eligible for copyright protection and this is a stance that the US Copyright Office has taken. However, to acquire said image, you also need specific prompts and those do contain the human creativity factor, but most of the generators available leave the prompts generated by an user open to everyone to see and copy. Ultimately, it is important to consider the potential implications of not protecting AI-generated images. For example, if AI-generated images are not protected by copyright law, this could pave the way for companies to mass-produce AI-generated images without compensating the creators of the original images. This could have a negative impact on the economic viability of creating original images and could stifle creativity.
While some believe that AI-generated images should be considered as original works, others believe that they should be considered as derivative works of the original images used to train the AI. I wish I could contribute my own solutions to all of the above aspects, but personally the only clear answer that comes to me is that prompts should be protected and not readily available like most generators make them be. As for the rest, well, after researching those issues I only became more and more perplexed, and I hope you as a reader will give those your own thought. After all, the debate about this copyright black hole is ongoing, and it is likely that it will continue to be unresolved for some time to come.
First of all, AI it is the future of our life. Nowadays we can easily see how this field is important and what role it plays in world economy system.
Especially, this area is very attractive for venture capitalists. In 2022 they have ploughed $67 billion into firms that claim to specialise in AI, according to Pitchbook, a data firm. Starting from the middle of 2021, the share of deals worldwide involving AI-related startups increased by 17%. I must say that this is very big breakthrough for such a period of time. Therefore it is not surprising that between January and October, 28 new unicorns(private startups valued $1 billion or more) have been minted.
It is a huge competition between the companies which are desperate to get their hands on AI talents. Derek Zanutto of CapitalG ,notes that large had spend years collecting data and investing in related technologies. So now they want to use this huge amount of data and AI gives them different ways to do that.
Unsurprisingly, that all huge organisations use AI to improve their software. For example, today Google uses AI to improve search results ,finish you sentences in Gmail and work out ways to cut the use of energy in its data centres, among other things.
Big companies quickly generate the plan how to sale some of Ai capabilities to their clients. Revenues from machine learning cloud service have doubled. In addition, upstart providers have wide spread, like Avidbots that leveraging data from a variety robot sensors.
In October Microsoft launched a tool which automatically wrangles data for users following prompts. All other huge companies may try to do something similar and several startups are already doing this. For example Google, presents in their video their first foundation model, which uses prompts to crunch numbers in spreadsheet and perform searches on property websites.
Other amazing thing that AI can do it is artificial colouring. In 2021 Nike bought a firm which uses such algorithms to create new sneakers design.
And the last example of how artificial intelligence is useful it is new technology of John Deere tractors which have some AI capabilities. This tractors can solve food problem in the word. IT is so important.
However, it is hard to say that AI is so profitable.
According to the McKinsey Institute’s survey: quarter of respondents to the survey said that ai had benefited the bottom line (defined as a 5% boost to earnings). The share of firms seeing a large benefit (an increase in earnings by over 20%) is in the low single digits—and many of those are tech firms, says Michael Chui, who worked on the study.
To sum up, this sphere is developing every day and become more and more necessary, but now it is not so great for large organisations in terms of increasing profits.
Artificial intelligence picture generation has drawn interest of many (me included) and has given rise to a lot of discussion. I assume many of you reading this blog post tried some of the engines yourselves or at least saw what they are capable of producing. At first sight it is very impressive, although the technology still has a lot of limitations, it is progressing rapidly especially that many codes are publicly available.
When it comes to Graphic Designers Industry, accordingly with IBISWorld, its market size for 2022 is estimated as $43.4bn which ranks this industry as 9th among the Global Business Activities industries. With such substantial size, it is inevitable that AI picture generation will find its place in this industry. Whether its influence will be big or small, it will most likely substitute or support many of the processes, in the same manner as increasingly more sophisticated graphic software did over the years. To back up my claim, I prepared for you a short case study.
When you need a graphic, be it an illustration, book cover, logo, or a physical depiction of the wild dream you had last night, if you were not an artist yourself, you would most likely look for outsourcing to one. Feverr is one of the websites that rallies freelancers of various fields, graphic artists included. I would like to present you the results of youtuber “Ten Hundred” after hiring artists on said website to make a graphic for him about his alleged dream for various prices. Below you will see a comparison of four pictures:
Two top ones were generated by me in nightcafe.studio which took me less than 3 minutes. Yes, they are of different styles, but I am sure that a person more familiar with the generators and one having more free access would be able to prepare a more fitting comparison. The two bottom pictures were ordered by abovementioned youtuber Ten Hundred for 155$ and 205$ going from the left, and he waited for the results around a week after paying extra for quick order execution. The funny part is, he explained what he was expecting to receive by text message, similarly as you type prompts to the current AI picture generators, and most of the artist he hired missed some of the details requested or added their own interpretations. Nevertheless, the mentioned order was quite detailed and abstract, I do not believe it would be easy for the AI to cleanly cope with such a prompt, and here emerges an opportunity for freelance artists, although not only, to use this new tool as a base of their works. On Fiverr alone there are already a lot of people offering their expertise in using the generators for 5 to 10$, but also artists that offer to generate and tweak or enhance AI generated pictures. While making a digital image, you will most often create layers, and even being able to quickly generate an original and detailed background scenery is a huge timesaver.
I personally believe that the interest of digital artists in this technology will grow more strongly than their aversion towards this potential competition and the industry in general will be affected.
As Christmas is fast approaching, we are starting to hear the holiday classics everywhere. From All I Want for Christmas at the Supermarket to Rockin’ Around the Christmas Tree on the radio – Christmas songs are virtually unavoidable.
But I’d like you to think of the artists behind these songs – most of Spotify’s Christmas Hits playlist[1] is comprised of songs recorded or written before the first manned mission to the Moon.
Naturally, many of the authors and performers listed in the credit sections of these songs are long gone – Bing Crosby died in 1977, Nat King Cole passed away in 1965 and Frank Sinatra departed in 1998.
Frank Sinatra source: http://enterate24.com/hace-104-anos-nacio-el-cantante-frank-sinatra/
It’s a shame that we won’t be able to hear any new songs from them.
But what if it doesn’t have to be that way?
That’s where OpenAI’s Jukebox comes into play.
Debuted in April 2020, the technology analysed over a million songs[2], along with their lyrics and metadata (release date, genre, mood) and is now capable of generating full tracks in the style of any well-known artist. The company shared a range of demos, designed to resemble artists such as Alan Jackson, Katy Perry, or Elvis Presley. Most notably though, the song that stands out is “Hot Tub Christmas”, in the style of Frank Sinatra. While the “recording” quality might not be perfect, the timbre of the “singer’s” voice is eerily similar to that of the legendary American singer.
Though the lyrics have been co-written by a language model and OpenAI researchers, the chord progressions and instrumental cohesion are very well replicated in the computer-generated mp3s. The team behind Jukebox is aware of the software’s faults, as “[…] the generated songs show local musical coherence, follow traditional chord patterns and can even feature impressive solos, we do not hear familiar larger musical structures such as choruses that repeat.”2
Jukebox doesn’t analyze the actual notes in the songs, but only relations between pitch over time. An upside of such an approach is the possibility of highly realistic human voice creation. For their future endeavors, OpenAI plans to integrate a note-to-MIDI technology which would detect the rhythms and exact notes, which would allow for a deeper, more natural, and precise song creation – perhaps with the use of software instruments or synthesizers for higher file and sound quality.
Jukebox, at this point, is treated by the music industry as a mere curiosity, with no real applications – even despite a new feature of creating an acapella file from user-generated lyrics being introduced. This dynamic might change in a relatively short time if Jukebox becomes able to create classically written songs, providing the notes, rhythms MIDI files behind them. With such possibilities, songwriters and producers could streamline their music creation processes and massively increase their output.
The current market situation is visualized by the fact that most of the investments poured into creative AI come from Venture Capital and Tech Corporations – not from the Music Industry.[3]
At this point, it does not seem like any songwriter or producer jobs are endangered. High quality audio files have incredibly many timesteps which encode data – a standard 4-minute-long song in a .wav 44.1 kHz file will contain over 10 million timesteps.[4] Currently, a song needs to be almost fully produced and designed by a professional before being rendered into such a complicated audio file.
The process of AI art generation is slowly being integrated into commercial culture, with the generator Midjourney winning the Colorado State Fair Fine Arts Competition.[5] Jukebox and similar technologies are often criticized for taking away the humanity out of art, while some perceive it as an opportunity to augment their creations through technology.[6]
“Théâtre D’opéra Spatial” – the AI-generated, contest winning piece of art source: https://edition.cnn.com/2022/09/03/tech/ai-art-fair-winner-controversy/index.html
To me, it seems inevitable that Artificial Intelligence will be widely used in the music industry – major labels will push for anything that can give them a competitive edge in business.
We must also take into consideration the legal implications of Jukebox.[7] Our laws don’t include AI “artists” and thus, there might be copyright implications. Who is the de facto author of such a song? The AI developer, or the person who entered prompts into the technology to create a specific tune? How do we split royalties for such songs? Furthermore, is it acceptable ethically to expand dead artists’ catalogues?
In conclusion: AI is slowly entering into creative arts, especially the music industry, thus expanding songwriters’ and producers’ output and possibilities. It appears that in this case, the risk of actual people being replaced by technology is lower than in easily automated and routine operations.
This time, I’ll ask the classic question: do you think that AI art is proper art? Should it be publicly disclosed that a song or a painting was generated through Artificial Intelligence?
Breast cancer is one of the modern world diseases that greatly influence women’s lives (0,5%-1% of the cases occur to men) with a high death rate – in 2020 out of 2.3 million women with breast cancer, 685 000 of them died. It is the most frequently diagnosed cancer among women worldwide. The key to combatting it in the early stage is by screening however the current methods as self-checking or mammalogy are seen as not accurate enough due to women’s unawareness of proper screening methods or the stigma of being physically tested by a doctor. With the rise of the importance of AI and women’s irritation, new possible solutions started to be introduced around the world.
In 2016, Geetha Manjunath, a data analyst from India, lost her cousin who died out of breast cancer. Geetha blamed the mammology method as it didn’t discover breast cancer in time. She stated that mammographs have high difficulties in discovering cancer among young women and that there needs to be some improvements.
“As I was working with multiple image modalities for other projects at Xerox, I chanced upon thermal imaging.” – Geetha Manjunath said.
She came up with the idea of combing thermal screening with AI. The whole process consists of thermal scanning the women and then comparing the results to the already existing pictures of patients with cancer with the help of AI to analyse loads of past cases and asses whether a pattern on a thermal picture could be a sign of early-stage breast cancer. Another advantage of Geetha’s project called Thermalytix is that is affordable, which is a major game-changer in a country like India where a lot of women are not affluent enough to be able to spend their savings on breast cancer screening. Another key factor, especially among young women is privacy. During the visit, nobody touches the patient and the doctor only sees a thermal image of the chest on the screen. It is also radiation-free and non-invasive so it doesn’t hurt and is not harmful to the body. So far, Geetha has screened over 75 000 women across India and plans to expand her innovative idea. Her mission is to make access to screening to every woman on the globe with the current progress of introducing her methods into countries like the Philippines and Kenya. She also started creating camps in poor areas of India to help poor women detect the disease before it’s too late, as they are the most vulnerable.
Yet, researchers alarm that in the current stage the are some challenges to using AI in screening breast cancer. Firstly, AI databases are currently limited in comparison to the desired accuracy – AI bases its prediction on the pictures that are already in the database, therefore any new cancer pattern or any other abnormalities might be not registered by AI. Secondly, the electronic medical database is still not fully updated and well organised in many countries, even those well-developed as well. It leads to poor sources for AI to create the right prediction. There would also be a need for a global medical easy-access software system for all of the hospitals, which is extremely hard to organise on a worldwide and national scale. Moreover, there would have to be some social trust towards the doctors who would be making their decisions based on AI results which might nowadays rise some doubts and reluctance. Following that, hospitals would have to make special training for the doctors to implement using AI in screening breast cancer which takes time and money.
The method is visionary and promising as it creates a comfortable way of detecting breast cancer conducted by a professional. It could minimise the scope of the problem drastically, helping all no matter their financial background. Yet, due to its early stage, there are some limitations as relatively small databases, the low popularity of medical data stored on the internet in many third-world countries and the question of AI deciding our health. Nonetheless, I believe there is a great future with this method and the right people and funds it can revolutionise the world.
It’s high time that we finally pivot away to other authentication methods rather than using infamously vulnerable alphanumerics to protect our private data.
It’s common knowledge that passwords are one of the most widely used authentication methods for protecting our private data, however, it may be a surprise to know how common they actually are. As of April 2022, there were roughly 300 billion passwords in use, which averages to around 38 passwords per person¹. Hence, it is safe to say that passwords have played a major role in the world of cybersecurity. But that needs to change. And I am not the only one who thinks it.
Giant Tech companies, such as Apple and Microsoft, have made plans to make passwords redundant by announcing their intentions earlier this year, ironically on World Password day, to implement new, universal passwordless sign-in methods, such as biometrics including face and fingerprint recognition, across all of their platforms and devices².
Most of us might already be familiar with these types of authentication methods as they are most often used to unlock our android and apple devices, confirm payments, and more.
But why should we change to passwordless authentication methods? What’s wrong with passwords? Read below to find out!
The beginning of passwords.
In 1961, a pioneer in the field of computer science, MIT professor Fernando Corbato, came across a challenge. Back in the 1960s, all professors at the MIT university were using a shared computer system known as the Compatible Time-Sharing System, or CTSS³. Therefore, all of their private files were stored in a single disk which would be accessed through a common mainframe. Worried about the fact that their individual files could be seen and accessed by anyone, Fernando came up with a solution – passwords. He gave each user a password with which they can only access their own files and no one else’s.
As time went on and computers became more accessible, passwords were, and still are, used as the main authentication method to protect private files due to their simplicity, which is now seen as one of its major flaws. Sure, some websites make it mandatory to have an alphanumeric password with special characters but they bring up their own set of problems and there’s only so much you can do to prevent unauthorized access to data through passwords, which brings me to my next point.
What’s wrong with passwords?
Here are the 2 major problems that occur with the use of passwords –
Passwords aren’t User Friendly – As mentioned earlier, an attempt to make passwords more secure by mandating users to include both upper and lower case characters, special characters, and numbers while also requiring a minimum password length, makes it less user-friendly. Here’s why – by making lengthy and complex passwords, not only are they hard to remember but as a result, we often end up saving them on our browsers/password manager (which can be hacked, stolen, and leaked) or end up resetting the password and using the same password across multiple websites…which makes it less secure.
Passwords aren’t Secure – It might be challenging to strike a balance between security and usability because a password that is easy to remember is also insecure, and a password that’s secure is harder to remember. Secure passwords might not be easily guessed compared to insecure passwords, but both types of passwords can be hacked and stolen through, for example, a brute force attack and can further be leaked or sold to third parties. Moreover, passwords can be forgotten which often ends up in resetting the password which can be troublesome if the same forgotten password was used for multiple websites.
Passwordless ways of authentication.
In order to abandon passwords as a form of security and authentication, we need to create and implement/use other methods of securing private data. One of these security methods is already being widely used, most commonly, to unlock devices – Biometrics.
Biometrics
There are two types of biometrics that are often used for authentication – fingerprints and facial recognition. It is said that no two individuals have the same fingerprints, hence, not only does this make this authentication method more secure but it also removes the need to remember complex passwords. Moreover, it’s a faster process and improves user experience by removing the need to remember your fingerprint. Although this security method is much harder to bypass, it is not impossible, as fingerprints can be copied and replicated even though it’s hard to accomplish⁴.
Facial recognition is another biometric authentication method that uses a person’s face to verify his or her identity against already existing facial data. Facial recognition can be used by any device with digital photographic technology. For example, all modern models of iPhones are equipped with a TrueDepth camera system, neural networks, and bionic chips which all work together to project and analyze thousands of invisible dots in order to construct a 3-Dimensional map of your face and take an infrared image of it⁵. Similar to facial recognition, this method is a smooth, quick, and efficient way of authenticating a user and protecting your files. However, like any good authentication method, it has its disadvantages. For example, poor lighting can affect the efficiency of the system and might require multiple attempts to unlock the device/files. The use of facial accessories, such as face masks, scarves, hats, and more, can also lead to multiple unsuccessful attempts, and eventually, the system might ask you to remove them. Nonetheless, fingerprints and facial recognition are definitely a securer and safer way of authentication when compared with passwords.
Passwordless Multi-Factor Authentication
No, I am not referring to the security code or one-time password you get when you finally remember the correct password after multiple failed attempts, only to find out there’s an additional layer that requires you to enter another password, making you more frustrated.
This type of passwordless authentication method depends purely on a second device and eliminates the use of generating another password in the first place, which could’ve been accessed on the same device. It is slightly dependent on the use of biometrics and here’s how. For example, to log into your account, all you have to do is enter your email address and the system will send a push notification to the mobile number that is registered with the email. Unlike a normal 2-Factor Authentication where you are required to enter a password in the first place, and a security code or one-time password is sent to your email address which can be accessed on the same device, this type of authentication method requires you to open the push notification and approve the login attempt through 2 different ways – you will either be asked something in the lines of “We’ve noticed a login attempt from ABC device. Is this you?” and you’re required to choose yes or no. The second way is that the notification will contain 3 different numbers and you have to select the number that matches the number that is displayed on the device you are trying to log in to.
The push notification itself requires you to unlock the phone in the first place using biometric authentication, hence, it adds an extra layer of security. Furthermore, hackers or other third-party users who want to gain access to your account will find themselves in a difficult situation as they would need access to your phone and you⁶.
The only disadvantage this possibly portrays is that it is more time-consuming when compared to simply entering a password or using biometrics. Other than that, it is still considered to be safer and more securer than passwords.
The challenges of going passwordless.
One of the major challenges of using passwordless authentication is that it requires you to first create an account with a password before having the option to choose the passwordless authentication method. Another problem is that passwordless authentication will not be possible on legacy and older systems as they simply lack the technology to do so. Hence, if a company wishes to switch to passwordless authentication, replacing these legacy systems will become a necessity and would cost tens of thousands of dollars to do so.
Furthermore, there are legal and ethical concerns⁷ with the use of biometrics as a method of authentication as companies may not secure their employee’s biometric data or users might be suspicious of the software used to recognize their biometrics as, for example, the camera might never have been turned off after recognizing their face, which is a breach of privacy as the company might be using the camera to surveil or spy on them and can also be selling the data to third parties which can lead to even bigger problems such as identity theft and fraud.
Conclusion
There is no doubt that going passwordless would be a safer and smarter authentication method, especially as it guarantees a frictionless user experience and removes the threats of all password-based attacks as attackers wouldn’t be able to use passwords to log in simply because they won’t exist. This includes the two most dangerous attacks – Phishing and Brute Force attacks. Brute Force attacks would not work as there would be nothing to steal and Phishers wouldn’t be able to steal login credentials as they simply would not exist.
For those of you who are determined to use passwords, and we might be stuck with them for a while, I recommend using a password manager as they offer strong encryption and act as a place to keep all of your passwords in without having the need to memorize them. They also hold features such as generating and changing passwords in one click, and more. Even though they offer their own challenges, such as once hacked, all of your sensitive data will be vulnerable or your passwords might be being sold to third parties by the password managing companies themselves without consent, it is the best option for those who use and will continue to use passwords. But not all of us will be able to afford or want to pay for it.
With developments in technology and cyberattacks following suit, it is necessary that the required changes are made in relation to cybersecurity and that includes the end of passwords. It will undoubtedly take a while for websites and businesses to change from passwords to passwordless authentication methods but that time isn’t as far off as you might think…
Some facts and figures
Here are some facts and figures to help you decide whether you should go passwordless. What do you think? –
90% of internet users fear that their passwords might be stolen¹.
More than 23 million people use “123456” (one of the most common passwords) as their password to protect their data¹.
78% of Generation Z have been found using the same password across multiple accounts and websites⁸.
73% of internet users believe that forgetting passwords is the most frustrating element of security⁸.
69.7% of internet users fail to update their passwords once a year⁸.
53% of internet users use only their memory to store and retrieve passwords⁸.
Only 35% of Americans trust password managers¹.
Every minute, 5-6 businesses become a victim of ransomware¹.
Bibliography
¹Krstic, Branko. “Impressive Password Statistics to Know in 2022.” WebTribunal, 6 Apr. 2022, webtribunal.net/blog/password-stats/#gref. Accessed 02 Nov. 2022.
²Bateman, Tom. “Big Tech Plans to Kill off Passwords Altogether. What next?” Euronews.next, 5 May 2022, www.euronews.com/next/2022/05/05/forget-passwords-apple-google-and-microsoft-say-you-won-t-need-them-at-all-in-the-future. Accessed 02 Nov. 2022.
³Holt, Rene. “A Short History of the Computer Password.” WeLiveSecurity, 4 May 2017, www.welivesecurity.com/2017/05/04/short-history-computer-password/. Accessed 03. Nov. 2022.
⁴Jirik, Pavel. “5 Popular Types of Biometric Authentication: Pros and Cons.” PHONEXIA Speech Technologies, 9 Sept. 2021, www.phonexia.com/blog/5-popular-types-of-biometric-authentication-pros-and-cons/. Accessed 04 Nov. 2022.
⁵Tillman, Maggie. “What Is Apple Face ID and How Does It Work?” Pocket-Lint, 4 Mar. 2022, www.pocket-lint.com/phones/news/apple/142207-what-is-apple-face-id-and-how-does-it-work. Accessed 04 Nov. 2022.
⁶Groeneveld, Rachid. “The Password Problem.” Nomios, 7 July 2021, www.nomios.com/news-blog/password-problem/. Acessed 04 Nov. 2022.
⁷Fernandez, Ray. “The Challenges Facing the Passwordless Future.” ESecurityPlanet, 25 Sept. 2022, www.esecurityplanet.com/applications/passwordless-challenges/. Accessed 04 Nov. 2022.
⁸Vojinovic, Ivana. “Save Your Data with These Empowering Password Statistics.” DataProt, 2 Nov. 2022, https://dataprot.net/statistics/password-statistics/. Accessed 05 Nov. 2022.
Honan, Mat. “The End of Passwords.” MIT Technology Review, 23 Feb. 2022, www.technologyreview.com/2022/02/23/1044953/password-login-cybersecurity/. Accessed 03 Nov. 2022.
Kinzer, Kelsey. “The Benefits and Challenges of Passwordless Authentication.” JumpCloud, 12 Jan. 2022, jumpcloud.com/blog/benefits-challenges-passwordless-authentication. Accessed 05 Nov. 2022.
Berhanu, Manny. “The Beginning of the End for Passwords.” FutureBusiness, 10 June 2022, future-business.org/the-beginning-of-the-end-for-passwords/. Accessed 03 Nov. 2022.
Rob. “The End of Passwords? Why the World Is Moving Away from This Traditional Method.” ROWND, 27 June 2022, blog.rownd.io/the-end-of-passwords-why-the-world-is-moving-away-from-this-traditional-method/. Accessed 05 Nov. 2022.
We’re approaching 2023. We can fly across the world in a matter of hours. We can communicate in real-time with anyone, anywhere on Earth. And now, we can make anyonesound like a white American.
As wild as it may seem, that is exactly what Sanas’ AI development does – the algorithm takes anyone’s voice as an input, and (with minimal delay) puts out a slightly robotic voice of the ‘standard’ English speaker – colloquially known as a white, educated U.S. citizen’s voice.
Why would anyone even use it?
As usual, the answer is money.
Sanas was designed to help in offshoring call-centers. It is twice as cheap to hire a worker from countries like Pakistan or India as it is to hire them from in the United States.[1] The company operates on the assumption that all the callers must do is read a script and carefully follow sales/customer handling instructions.
Sanas’ president Marty Sarim stated that ‘We don’t want to say that accents are a problem because you have one, they’re only a problem because they cause bias and they cause misunderstandings.’[2] Nevertheless, the company has been flooded with accusations of perpetuating racial stereotypes and reinforcing racial bias.
For one, Nakeema Stefflbauer (AI and tech angel investor, CEO of women-led computer programming group FrauenLoop) described Sanas’ mission as a form of ‘digital whitening.’[3] She believes that the company doesn’t emphasize comprehension as much as it emphasizes comfort – for those who do not want to understand, empathize, or acknowledge individuals of different backgrounds, and, as a result, with different accents.
There has also been outrage among the company’s target group: Mia Shah-Dand (the founder of Women in AI Ethics; an immigrant from India with a non-American accent) found the company’s goal ‘very triggering’. She slammed Sanas for trying to discard people’s uniqueness and for propagating the message that they’re ‘not good enough’.3
Three of Sanas’ four founders (Shawn Zhang, Maxim Serebryakov and Andrés Pérez Soderi), who met while studying at Stanford source: https://edition.cnn.com/2021/12/19/us/sanas-accent-translation-cec/index.html
Naturally, Sanas’ board and founders have addressed these claims:
90% of their employees, and all 4 of the founders are immigrants.1 Additionally, two of the board members – Massih Sarimad and Sharath Keysheva Narayana – have previously worked in call centers and witnessed racial abuse in the workplace first handedly.[4]
Sanas’ product is allegedly designed to be operated only by the call center worker – so that only they can switch the program on or off and have full autonomy in deciding whether they want their accent to be translated. While this seems like a rational idea, it is highly unlikely that it would actually be implemented – after all, call centers are very formalized structures with specific instructions. Thus, it is doubtful that managers would opt for their workers to have such high degree of ‘freedom’.
So far, Sanas has raised over 37 million USD in investments,[5] and has ambitious plans. Their aim is to introduce many more accents into their technology, to allow for seamless communication, as if everyone were your local. The company also plans for expansion into the entertainment industry – Maxim Serebryakov (the CEO of Sanas) said that “There are also creative use cases such as those in entertainment and media where producers can make their films and programs understandable in different parts of the world by matching accents to localities”.
So, what’s the verdict?
Personally, I don’t believe that Sanas’ operations are inherently racist – though it might seem quite questionable at first. Considering the fact that most members of their team are immigrant, they are the ones to truly understand the pain of being racially discriminated against for their accents or appearance. If this is a solution that will allow for the reduction of racist incidents and decrease of stress among call center employees, then so be it. It is worth noting that things can turn upside down quickly, should Sanas enable an option for call center managers to force the usage of this technology on their employees.
Should things pan out the way Maxim Serebryakov and the rest of the board say, Sanas could be a powerful tool for mitigating racist remarks and for optimizing costs and performance of call center outsourcing. The only way to find out is to wait and see.
Would you be interested in trying Sanas? Do you think having an American/standard English accent on online calls and meetings would help you in your career?
Have you ever been thinking about the reason why social media was created? Why did people become so engaged in it extremely quickly? Sometimes I am wondering whether the emergence of social media was exactly a step toward social development or in reality it initiated an inevitable threat to the whole population.
Let’s consider Facebook – the most massive social network in the world that gave birth to an unbelievable number of internet communities. Once Facebook introduced its mission statement – the goal to provide thousands of people with the opportunity to stay connected with the world, users got accustomed to it immediately. But the mission of Facebook evaporated as quickly as people became obsessed with this social network. Facebook produced obsession. By using and using it again, people developed a habit of scrolling their feeds every day, that was a certain form of a drug for them. And while having been totally absorbed in the news feed, people did not notice one crucial thing – their behavior, consciousness and emotions were deliberately manipulated. It is not hard to guess that the primary purpose of Facebook’s creation was to control people. Social networks are existing with the strict mission of keeping people’s desires, preferences, intentions, goals, habits and even fears under control. They know us better than anyone else, playing the role of our personal diary. Have you ever noticed that people are much braver to express their opinion particularly via social media, since they feel the freedom for their thoughts to be heard and not punished? Data analysts of Facebook know it for sure. They are able to detect and sort individuals accordingly to their temperament and character features as a result of surveilling and analysing their requests, comments, messages and contributions to society. With the help of Artificial Intelligence systems, developed by Facebook’s data analysts, every user’s individual profile is created to adjust their behavior by producing posts and advertisements, that perfectly fit their desires and interests. People get imprisoned in social networks without comprehending it and are gradually turning into robots who are guided to buy certain products and services or to read certain pieces of news intended especially for them. However, consumer and social behavior is not the only thing, being under the control and manipulation of AI. Artificial intelligence systems significantly affect our morals, preconceptions and values.
I would like to elaborate on the scandal of Facebook with the Cambridge Analytica campaign. In 2015 data of numerous Facebook users were collected without their consent by the data analytics firm in order to create a system that affects people’s choices regarding the presidential election. By spreading perfectly-designed targeted polls, advertisements and posts, Cambridge Analytica managed to influence the consciousness of voters and change their opinion about the election. An extremely similar situation is evolving nowadays in Russia, where citizens are experiencing severe brainwashing caused by the flow of posts and news, developed by the Russian government, which eventually leads to the inability of Russians to consciously perceive information about the war in Ukraine. Because of extreme manipulation tools they are blind to the hazardous nightmare that is happening to millions of innocent Ukrainian people. Unfortunately, these examples of manipulation caused by social media are limitless. Social media users are doomed to be the victims of various types of propaganda, promoted by social networks.
So what is the real purpose of social media existence? Social media is an efficiently-designed and developed digital weapon. By applying Artificial Intelligence , workers of Facebook, Instagram or Twitter are capable of influencing the consciousness and actions of millions of individuals. With the help of Artificial Intelligence systems, social media transforms people into robots, who unintentionally do things they do not want to. It exterminates the autonomy of people’s opinions and mindsets. So is AI really a step toward our world’s development or is it the beginning of humanity’s “death”, the vanishing of people’s independence and freedom? Maybe AI was intended not for creating robots, but for turning people into them? Maybe its most crucial goal was not to alleviate human life but to simplify the control over people, the control of their thoughts and actions? We will probably see it. Or not, because we won’t be able to figure it out, being already under control.
Since the first commercial flight which was in 1919 a lot has changed. Initially all of the things associated with flying were planned and done manually. Now when AI exists many of those tasks can be done automatically which results in improvement of both passengers and the air traffic flow. This technology can be also used in supporting ground services.
Why airlines and airports collect so much data?
Nowadays a lot of data is gathered in the aviation industry. It’s not only about technical aspects of planes and traffic management but also about passengers satisfaction. As we know customers in this case travellers are in this industry are the most important factor, because of how much money they spend every month or a year on flying. That’s why airlines and airports are now putting pressure on collecting feedback from passengers to improve their services.
How airlines use AI and Data Science to improve services?
With so much data gathered airlines can introduce it to various AI systems to get the work done for them, which is faster more accurate and definitely more convenient. There are many ways of using AI but let me focus on 4 that are in my opinion the most interesting to know about.
1.Predictive maintenance
For a long time airlines are struggling with a problem of flight delays or cancellations due to unplanned maintenance works. If something like that happens they are obliged to pay compensations for passengers that are stuck in airports. That’s why they have introduced predictive AI system which helps to monitor the health of specific parts in an aircraft. It also suggests mechanicians when such a part will need to be changed and how long it takes to do so. What’s more predictive algorithms can predict potential failures on a plane before they actually happen. With this predictive maintenance applied airline can reduce it expenses significantly. However AI can only assists in the maintenance process, but it won’t replace essential aircraft inspections.
2.In-airport self-service
In this area Covid 19 has changed a lot. Pandemic has speeded up the development process of self-service devices such as self-check-in machines. But that were the first steps in making a passengers trip automated. Today, airlines provide solutions that allow passengers to travel with using self-use devices from checking to boarding. For example during security check technology analysis your face and comperes it with the scan of your document that you need to put on a scanner. What’s more it also checks if you aren’t chased by a police. All those technologies are made to reduce the check in time and to improve passengers satisfaction. However traditional ways will still exist.
3.Flight and fuel optimalization
As you already know flight delays might be very costly for airlines, that’s why there are doing everything to avoid such situations. It’s not easy to plan and schedule everything considering all aspects connected with flight such as weather conditions and air traffic flow. Now AI analyses real time data such as traffic flow, weather conditions, turbulence and many other variables so that dispatchers can make better decisions. It is also meant to find optimal flight routes to decrease the amount of emission of carbon dioxide and also to reduce the fuel consumption.
4.Dynamic ticket pricing
If you ever booked a flight ticket you might have noticed that prices differ day after day. It differs because of many variables such as: departure time, destination, flight distance, and the number of available seats. The cost of the same ticket can change minute by minute. That’s because of airlines use AI system which is called dynamic pricing. It’s a technique of setting new prices so that they are the most profitable, unfortunately only for airlines.
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To sum up shortly AI is a tool that helps airlines to reduce their costs and improve their services. However it won’t always be the main way of dealing with problems in some aspects of aviation. Personally i think it enchances the way of traveling for passengers.
Let me know what are your thoughts. If you want to find out more about AI use in aviation industry i recommend you watching this video from altexsoft.
Artificial intelligence has made our lives much easier since its inception. In the real world, everything is so connected with new technologies that it is simply impossible to imagine life without AI. And without any doubt, the contribution of technology to the field of medicine is the most important.
So, the issue of my talk, as it is easy to guess by the heading, is the contribution of AI to medicine.
A specially developed device in the future will be able to detect and predict the risks of heart disease.According to the British Journal of Ophthalmology, it soon will be quite possible to produce special cardiovascular screenings. In just 1 minute patients will be able to learn about the risks of heart disease. There will be no need to conduct any additional blood tests and similar frauds. Everything will be reduced to the greatest efficiency and the minimum time. This is how artificial intelligence works!
Personally, I think it’s a very cool idea. Firstly, nowadays cardiovascular diseases are very common. This is a real problem not only for older people. In addition, that’s a common fact that after the Covid-19 many people began to have heart problems. It turns out that there have become more issues concerning health.
The task of scientists is to save human lives. In many cases, medical care for late detection of the disease is already ineffective. And nothing can be done! In addition, high-quality medical care is an expensive thing. As a result, poor people do not get the necessary medical examinations. A very good thing about this new tool is that the inventors talk about its cheapness. I believe that quality medicine should be available to all segments of society, regardless of wealth.
The tool studies the blood vessels that are located in the retina of the eye. The tool takes into account various changes, makes all kinds of measurements. It turns out that blood vessels in retina and heart are closely connected, which provides a special opportunity to determine the state of the heart and even predict all sorts of risks through the retina.
Of course, this is very convenient. Any analyses require time, specified conditions, reagents or equipment. It seems to me that using this software will require less resources and human’s participation.
After all, I think it’s a wonderful invention. So far, of course, this is just an idea, confirmed by several studies. It will be quite difficult to transfer the code to real medicine. But still, artificial intelligence plays for the benefit of humanity and this is wonderful.
