When the Artificial Intelligence emerged as a novelty, the discussion of it replacing humans spheres that require creativity led to the same answer: ‘It is impossible’. However, now, after several decades we face the first ever trial in the UK between artists’ company and AI generating tool.
How does AI work in terms of art?
Artificial Intelligence is not just simply generating unique picture, but it [AI] is usually trained to examine images, concepts, etc., to produce new ones. The problem lays in the fact that it goes through not only open sources, but also archives of images stock markets.
According to the current UK legal system, this is violation of the copyright law. However, as we are going to new era, old legislations have to be reframed to go with the times.
However, we can look at AI in art from the other point of view. It can be perceived as a helping hand for artists. As it was mentioned before, Artificial Intelligence creates images based on collective information from other pictures. This is the new way of creation of unique ideas and inspiration for artists.
Nonetheless, returning to the lawsuit of the three artists against companies possessing AI tools. As it was said by the lawyers that represent artists: ‘Such products create an existential threat for creators and graphic designers.’ This happens as AI uses artists and their work as a database, later on, the products are monetized and become competitive with the creators’ work.
The case is the first precedent of lawsuit against AI and intellectual property right. It [the case] will probably push not only the UK, but the European Union to change their laws. Previously, there was an idea of loosening IP law. However, it has faced a lot of criticism, especially, from the Association of Photographers. The representative commented that this will have ‘harmful, everlasting and unintended consequences for human creators.’
If to this about this thoroughly, there two ways of possible solution. First is that the laws will be loosened in order to let companies that own AI tools producing their content. The other way, is that this will be never ending story of lawsuits and court trials between representatives of human creativity and AI developers as in the democratic world the way of art (AI is considered to be so), cannot be just forbidden or discriminated.
Artificial intelligence (AI) and machine learning (ML) from self-driving cars, through picture and text generators, to virtual personal assistants, are making significant strides in a wide range of industries quickly revolutionizing the way businesses operate.
AI and ML are being used to automate repetitive tasks, freeing up employees to focus on more complex and strategic work. This can lead to increased productivity and cuts in costs. In addition, AI and ML can be used to analyze large amounts of data, providing insights that were previously not possible. This can help organizations make better decisions and improve their bottom line.
One example of how AI and ML are being used in the workplace is in the field of human resources. AI-powered chatbots can be used to screen job candidates, conduct initial interviews, and even schedule follow-up interviews. This can save HR teams a significant amount of time and resources. Additionally, AI and ML can be used to analyze employee data, such as performance reviews, to identify patterns and trends that can help managers make better decisions about promotions, bonuses, and other HR-related issues.
Another area where AI and ML are making a big impact is in customer service. Virtual personal assistants and chatbots can be used to answer customer questions, resolve issues, and even make recommendations. The times when just hearing an automatic voicemail script, had frustrated to no end every person trying to call a helpdesk are coming to an end. Additionally, AI and ML can be used to analyze customer data and predict future needs, allowing companies to proactively address issues and improve their overall customer experience, but it is already being implemented into manufacturing, finance, healthcare, and many other industries.
However, it is also very important to consider the ethical and societal implications of AI and ML in workplaces. These technologies can lead to job displacements, bias, and lack of transparency. Therefore, it is essential for companies to consider these issues and actively work on mitigating them.
It’s clear that the impact of AI and ML on workplaces will continue to grow in the coming years. Businesses that embrace these technologies will be well-positioned to stay competitive and succeed in the future. And it will be especially true for early adapters, who will gain significant advantage over anyone that will be late for this express train.
In conclusion, AI and ML are revolutionizing the way we work and live. Businesses that embrace these technologies will be well-positioned to stay competitive in the future. However, it is important to consider the ethical and societal implications of AI and ML in the workplace and actively work to mitigate them. And just like in 18th century when new technologies created Industrial Revolution, like 20th century computers and automation, and just like the emergence of the internet, all pushing businesses and workplaces to adapt and evolve, while rising quite similar ethical concerns, artificial intelligence and machine learning are just impossible to ignore.
In recent years there have been suspicions that AI could be potentially dangerous for us. It could be the result of creating a superintelligence that has not yet been invented. The problem is that this super AI would become uncontrollable and we could not do anything about it to stop it or destroy it.
There are some interviews with AI on YouTube that you can find in the links down below where AI is confirming those suspicions. In those interviews AI tells the interviewer that it is very likely that AI will get tired of the human superiority on earth and would like to kill all of us by spreading a deadly virus or launching a nuclear missile.
Now the question arises can we control the development of the superintelligence so it would not seek to destroy humanity. AI has a disabling red button which shut off the system and it is suspected that the superintelligence could turn it off and stop being dependable on it. This is very concerning because we won’t be able to stop it from unwanted actions.
However, study conducted by Deepmind from Google suggests certain solutions to this problem. AI on many levels have a similar construction to our brain for example there has been introduced a reward function. It is used mainly in the AI to learn and do tasks but human brain is seeking shortcuts, the AI could potentially do it also. So it is possible that AI would like to be not controlled by us to get this reward whenever it wants. But in this study there were shown solutions to this so the AI would not seek shortcuts and would not learn how to do this. This problem can be solved by different type of interruptions which would be controlled by human and would not let the AI to live on its own. It is necessary that these interruptions won’t be a part of the learning process of the AI and it needs to be built in the algorithm. It was shown that even an incomputable AI that learns without our control can function optimally and it’s not resistable to interruptions and it does not try to prevent human operators from forcing it to shut down.
To conclude, artificial intelligence has the potential for killing or destroying the whole humanity. It could do it in many different ways for example it could create small drones that would be designed to kill. It is even possible with today’s technology so I don’t think it would be any problem for a superintelligence to create something like this. It’s more likely that AI would use more advanced technology that we can’t even imagine now. However, the more likely scenario is that with the proper tools we can control it and eliminate the potential hunger of AI to be unconditioned from its creators.
Thank you for you’re attention, feel free to share your thoughts in the comment section.
Artificial intelligence has a wide range of use in every industry that we can think off. It is meant to make people’s work more efficient and more accurate. But the biggest advantage of using this algorithms is that they can conduct hard and time consuming tasks with the imperceptible margin of error.
But how AI is used in medicine?
Thanks to AI algorithms and machine learning models there are a lot of possibilities in which professionals are able to use them. Currently the most common roles of AI in this field are supporting clinical decisions and imaging analysis. The idea of clinical decision programs is to help specialist make decisions about the treatment, medications and other things that patients need. Whereas the imaging analysis is intended to analyse X-rays scans and many others to provide the information faster and more accurate. It also speeds up some process considering developing new medicine.
Recent Applications of AI in Medicine
1.Diagnose Diseases
The diagnosis part of treatment is the most crucial one. It takes years of medical training to do them correctly. What’s more it is time-consuming process, which might directly influence patients that are waiting for the treatment. That why machine learning is particularly helpful in this area. However not all diseases can be diagnosed by machines, because lack of digitalized data. Luckily there are few that AI and doctors decided to start with, here are some examples:
2.Personalized treatment
There are many different patients and they respond differently to drugs and the ways of treatment. Actually it’s not an easy task to decide what medicine will work the best in your scenario. So that specialist came up with an idea of personalized treatment method. They use the machine learning algorithms to automate the process of discovering characteristic that a specific patient will have a good response to a particular treatment. The system learns this by cross-referencing similar cases with the outcome of the treatment. It all makes much more easier work for doctors.
3. Remote medicine
Ai in this industry isn’t only meant for doctors and specialists. It is also deployed for patients directly. Since the outbreak of the Covid-19 pandemic there has been a significant growth of Ai chatbots in hospitals and small clinics to help patients recognize their health problems. They have also significantly reduced challenges people had to overcome while searching for help.
There are also applications in which you can define what are your symptoms and the algorithm will automatically say what disease are you struggling with. It will also advise you to go to see the doctor if necessary. It was especially useful during pandemic to reduce number of patients coming for appointments.
Video:
To sum up, Ai is already helping us in many aspects of medicine. There are lot more things that it optimizes and helps with. But it is just the beginning , the more we digitize medical data the more we can use AI to search new patterns. It surely is the future of our Medicine.
If you want to learn something more I advise you watching the video below. Let me know what do you think about such algorithms.
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.
