In this insight, we look at what ‘Universal Basic Income’ is, how it relates to the tech industry, its potential benefits and pitfalls, plus what similar ideas are being discussed and explored.

UBI 

Universal Basic Income (UBI) is a policy proposal in which all individuals in a given society receive a regular, unconditional cash transfer from the government, without any means-testing or work requirements. This income is intended to provide a basic level of economic security and enable individuals to meet their basic needs, regardless of their employment status or other sources of income.

The idea of UBI has gained increasing attention in recent years as a potential solution to a range of social and economic problems, including poverty, income inequality, and automation-driven job displacement. Supporters argue that UBI could reduce poverty and inequality, promote entrepreneurship and creativity, and provide a safety-net for those who may be left behind in a rapidly changing economy.

Supporters In The Tech World 

There are some high-profile tech industry supporters of UBI. These include:

– Elon Musk, CEO of Tesla, and SpaceX, has in the past been a vocal advocate for UBI, arguing that it is necessary to address the potential job losses caused by automation.

– Mark Zuckerberg, co-founder, and CEO of Facebook, has also expressed support for UBI, calling it a “safety net” that could help support people as the economy evolves.

– Sam Altman, former president of startup accelerator Y Combinator, and now CEO of OpenAI (ChatGPT’s creators), has been a strong advocate for UBI.

– Andrew Yang, former presidential candidate, and entrepreneur, made UBI a central part of his campaign platform, arguing that it was necessary to address the economic challenges posed by automation.

– Chris Hughes, co-founder of Facebook, has also expressed support for UBI, arguing that it could help address inequality and provide a safety net for those who are left behind by technological change.

Tested 

Several countries and cities around the world have implemented (or are testing) variations of UBI, including Finland, Canada, and Stockton, California in the United States.

How Does UBI Relate To The Tech Industry? 

The advancement of AI has the potential to significantly disrupt the labour market, particularly in industries where routine tasks can be automated. This could lead to significant job losses and wage stagnation for workers in these industries. At the same time, AI has the potential to create new industries and job opportunities in areas such as data analysis, software development, and robotics.

A Safety Net 

The potential impact of AI on the labour market has strengthened the argument for universal basic income, particularly in the tech sector. As jobs are increasingly automated, workers may find it difficult to find employment that pays a liveable wage. Universal basic income could provide a safety net for these workers, ensuring that they are able to meet their basic needs while they retrain or search for new job opportunities.

To Encourage Innovation 

Additionally, some advocates of universal basic income argue that it could encourage innovation and entrepreneurship in the tech sector. By providing a basic level of economic security, individuals would be more free to take risks and pursue their passions, without the fear of financial ruin. This could lead to more startups and new technologies being developed, which could in turn create new job opportunities.

Criticism 

While the idea of Universal Basic Income (UBI) has gained support from many, there are also several criticisms of the concept. Here are some of the main ones:

– Cost. One of the most significant criticisms of UBI is its cost. Providing a basic income to all citizens could be extremely expensive, with some estimates suggesting that it could require a significant increase in taxes or cuts to other social programs.

– Work Incentives. Critics argue that UBI could disincentivise work, as people would have less need to seek employment if their basic needs were already met. This could lead to a decrease in overall productivity and economic growth.

– Inflation. Providing a basic income to everyone could increase demand for goods and services, which could lead to inflation and a rise in prices. This could offset the benefits of UBI and reduce its effectiveness.

– Social Stigma. Some critics argue that UBI could create a stigma around receiving government assistance, which could discourage people from seeking employment or pursuing other opportunities.

– Funding Sources. There is also debate around the best way to fund UBI, with some advocating for tax increases on the wealthy, while others argue for a reduction in other social programs. Finding a politically feasible funding source may be a significant challenge.

– Implementation Challenges. Critics also point to potential implementation challenges of UBI, including the need for robust administrative systems to ensure that payments are made efficiently and accurately, plus the potential for fraud or abuse.

These are just a few of the criticisms that have been raised about UBI, as they highlight some of the challenges and complexities involved in implementing such a policy.

Just One Solution 

However, it’s important to note that universal basic income is just one potential solution to the challenges posed by AI and automation in the labour market. Other policy solutions, such as education and training programs, could also play a role in helping workers adapt to changing economic conditions.

Similar Ideas 

There are several similar ideas to Universal Basic Income (UBI) that are being explored by policymakers and academics. Here are some of the most prominent:

– Negative Income Tax (NIT). This is a tax policy proposal that provides cash payments to low-income households that have negative tax liabilities. The amount of the payment is determined by the household’s income, with those earning the least receiving the highest payments.

– Guaranteed Minimum Income (GMI). This is a similar policy to UBI, but it is targeted specifically at individuals and households that fall below a certain income threshold. The payment amount is determined by the individual’s income, with those earning the least receiving the highest payments.

– Conditional Cash Transfers (CCT). This is a policy in which cash payments are made to individuals or households on the condition that they meet certain criteria, such as sending their children to school or attending job training programs. The aim of CCT is to incentivize behaviour that leads to long-term economic mobility.

– Basic Capital Income (BCI). This is a policy proposal that would provide a one-time payment to all citizens when they reach adulthood, which they could use to invest in education, training, or entrepreneurship. The goal of BCI is to help individuals build wealth and increase their economic security over the long term.

What Does This Mean For Your Business? 

UBI is a policy proposal that has gained increasing attention in recent years as a potential solution to a range of social and economic problems, including poverty, income inequality, and automation-driven job displacement. The tech industry has shown support for UBI, with high-profile figures such as Elon Musk and Mark Zuckerberg advocating it. The potential impact of AI on the labour market has strengthened the argument for universal basic income, particularly in the tech sector. While UBI has its critics, it is important to note that it is just one potential solution to the challenges posed by AI and automation in the labour market. Other policy solutions, such as education and training programs, could also play a role in helping workers adapt to changing economic conditions. There are several similar ideas to UBI that are being explored by policymakers and academics, including Negative Income Tax (NIT) and Guaranteed Minimum Income (GMI). It is important for UK businesses to stay informed about these policies and to consider the potential impacts they could have on the labour market and the wider economy.

Following Twitter’s announcement two months ago that it will be charging a minimum of $42,000 per month to enterprise users of its API, Microsoft is dropping Twitter from its advertising platform.

What Is The Microsoft Advertising Platform? 

The Microsoft Advertising Platform is a digital advertising platform that enables businesses to create and run advertising campaigns on various online channels, including Bing search engine, Microsoft Advertising network, LinkedIn, and other partner sites, such as Twitter (up until now).

With the Microsoft Advertising Platform, businesses can target their audience using various options such as location, age, gender, interests, and more. They can create different types of ads such as text ads, shopping ads, and display ads, plus set their bidding strategy to compete for ad placement on relevant search results pages or partner sites.

The platform also provides performance metrics and analytics to help businesses measure the effectiveness of their campaigns and make data-driven decisions to optimise their advertising efforts. It also offers tools for audience segmentation, ad optimisation, and retargeting.

What Did Twitter Say About Charging? 

On Feb 2, Twitter announced “Starting February 9, we will no longer support free access to the Twitter API, both v2 and v1.1. A paid basic tier will be available instead.” 

Following some to-ing and fro-ing on the decision and a delay over a major twitter outage, Twitter is reported to be putting its formerly free API behind a paywall by offering three levels of Enterprise Packages to its developer platform. The price of the packages have been reported as:

– The cheapest package – access to 50 million tweets per month for $42,000 a month.

– Access to 100 million tweets per month for $125,000

– Access to 200 million tweets per month for $210,000.

– In February, Twitter began charging for the data it collects from “hundreds of millions” of users, with a basic plan starting at $100 a month.

What Is The Value To Enterprises of the Twitter API? 

The Twitter API is a set of programming tools and protocols that enable developers to access and interact with Twitter’s platform and data. The API allows developers to build applications that can read and write tweets, access user profiles and follower lists, and perform other tasks related to Twitter’s functionality.

The Twitter API can provide significant value to developers and businesses in a number of ways, including:

– Data Access. The API allows developers to access Twitter’s vast data set, including tweets, user profiles and trends, which can be used to build new applications, perform research, and gain insights into user behaviour and preferences. Twitter says, “Twitter data are among the world’s most powerful datasets.” 

– Social Media Management. Twitter’s API can be used to manage social media accounts, including scheduling tweets, monitoring mentions, and responding to messages.

– Marketing. The API can be used to create targeted marketing campaigns, track engagement and sentiment, and measure the success of campaigns.

– Customer Service. Twitter’s API can be used to provide customer support and respond to inquiries and feedback from customers.

Outprices Almost Everyone + Limited Dataset 

Critics have argued that even the cheapest plan looks like it will outprice most current users.

Also, whereas Twitter’s free API access gave researchers access to 1 percent of all tweets, under the new pricing plans, caps will mean that users of the paid for API will only have access to 0.3 per cent of Tweets.

Critics have also pointed out what a steep increase this appears to be – $500,000 per year for a smaller amount of data, and that it’s not clear which users the packages are aimed at (since they may be unaffordable to most).

Musk Hits Back – Says Will Sue 

Following Microsoft’s announcement that it is dropping Twitter from its advertising platform, Twitter’s head Elon Musk hit back by threatening to sue Microsoft alleging that it has “trained illegally using Twitter data.” 

What Does This Mean For Your Business? 

Microsoft dropping Twitter from its advertising platform will be an inconvenient blow for ad buyers who will not be able to access their Twitter accounts through Microsoft’s social management tool. The huge charging hike (from zero to $500,000 per year) for those wanting to use Twitter’s API (with less data to work with) looks likely to price even larger enterprises, as Microsoft has demonstrated, out of the market and could force them to seek other ways to assemble their targeting data. This is likely to be potentially risky and costly for them too since, as Twitter boss Elon Musk once pointed out, Twitter is the “the de facto town square” and the data accessed by enterprises through the API still has some real value.

For Twitter, this latest attempt at finding a fast way to generate another much-needed revenue source may have back-fired and Musk’s growing frustration appears evident in his threat to sue Microsoft. It follows some other major companies (e.g. Apple) recently halting advertising on the platform over moderation concerns and, in a recent TV interview, Musk said that he could be willing to sell the company if the right person came along. The Twitter/Musk saga therefore looks likely to carry on into the near future.

A report in the Financial Times (drawing upon an internal Google Presentation) claims that Google plans to use AI to generate new advertisements, drawing upon those already created by humans.

Creates The Ads For You 

The use of generative AI will mean that advertisers will only need to supply a small amount of creative content as the basis for adverts ( e.g. key points in text, details of the target market and goals, images, and videos) and AI will be able to construct the various finished adverts as necessary. It was reported that Google Ads ran a test of using AI to create ads early this month.

Google already uses AI in its advertising in a lesser capacity to create simple prompts to encourage users to make purchases.

Performance Max 

It’s been reported that the generative AI will be part of ‘Performance Max’, Google’s new goal-based, conversion-boosting campaign type that allows advertisers to access all their Google Ads inventory from a single campaign. Google says Performance Max “combines Google’s automation technologies across bidding, budget optimization, audiences, creatives, attribution, and more.” 

Concerns  

It was reported that at the presentation, concerns were expressed about how Google would address known issues in generative AI such as disinformation, phishing attempts, and cybercrime. The point was also reportedly made that AI is simply optimised for converting new customers and doesn’t have an understanding of truth.

Google responded by saying that ‘guardrails’ would be put in place to address those issues on rollout.

Bard And More

Last month, Google began the rollout of its generative AI chatbot answer to OpenAI’s ChatGPT ‘Google Bard.’ Google is also planning a new AI-powered search engine and is bringing generative AI to its Workspace suite in Google Docs and Gmail.

What Does This Mean For Your Business? 

For advertisers, being able to use generative AI to construct multiple ads targeting different audiences quickly and intelligently with different goals from just a small amount of creative content could bring several benefits. As well as saving time and money, this increased automation and sophistication could also result in higher conversion rates, more effective marketing, greater ROI and profitability and a possible competitive edge.

It may also help businesses to discover new opportunities and ad strategies. On the flip side, despite Google’s apparent assurances that ‘guardrails’ will be in place, there are still concerns that generative AI could work with falsehoods or disinformation and that there may be some issues with the process (it’s very early days), which could reflect badly on advertisers. That said, if it’s as impressive as other generative AI experiences (e.g. ChatGPT), then it’s an exciting and welcome prospect. If the results are good and it’s popular, it could also serve Google well at a time when ad spending is in a bit of slump.

Ripple Energy has announced that it is creating the UK’s first c-owned solar park, allowing those who buy shares to benefit from green electricity, money off bills, and the feelgood factor of the climate and environmental benefits.

Where?

Ripple Energy says the new ‘Derril Water Solar Park’ will be on a 175-acre site in the Torridge district of Devon, 1.2km southwest of the village of Pyworthy.

What? 

The new solar park will have about 70,000 solar panels, giving it the potential to power around 14,000 homes with cheap green power.

When? 

Ripple says that the co-ownership share offer, which is open now, will close in mid-May and the park will be operational by late summer 2024.

How? 

People can buy shares in the cooperative society that will own part of the Derril Water Solar Park with shares starting at £25. The co-owner’s electricity supplier then buys their share of the solar park’s electricity and supplies it to their home or premises via the grid and automatically supplies the savings to their electricity bill.

The savings will be equal to the wholesale value of the power generated minus the operating cost of the solar park, multiplied by the co-owner’s share of the generation.

How Much? 

Ripple says, for a typical home, the cost is around £3,000 (paid on application) which buys enough of the solar park to generate 100 per cent of their electricity needs for 40 years. The minimum ownership is £25, and the maximum owners can invest is what would meet 120 per cent of their electricity needs. Ripple estimates that the effective rate of return will be 5 per cent over the 40-year operational life of the solar park with a member paying about £3,000 to get £170 as savings on their electricity bills a year.

The Benefits 

Some of the many anticipated benefits of the solar park include:

– The environmental and climate benefits of a saving of 19,000 tonnes of CO2 per year which is the equivalent of taking 12,250 cars off the road or the work of 6,785,000 trees.

– Savings on electricity bills and providing a cheaper alternative to solar panels for the house (up to 50 per cent cheaper than rooftop solar)

– The feel-good factor for co-owners of knowing that they’re reducing their carbon footprint as well as directly increasing the UK’s renewable energy capacity.

– It’s a fully portable scheme i.e., co-owners can take it with them if they move.

– Ripple says other benefits will come from the site acting as a host for ecological and biodiversity enhancements e.g., new bee banks, wildflower meadows and hedgerows.

What Does This Mean For Your Organisation? 

This co-ownership project is an example how the demand for green energy in addition to cost savings is creating new options for consumers – this is a co-ownership project rather than a green tariff. As Ripple points out, land use today has become more of a balance between ensuring food security, maintaining biodiversity, infrastructure demands and addressing the climate crisis. This type of scheme, a first in the UK, looks like it could benefit domestic and business co-owners by meeting a number of important needs and could be the shape of things to come as solar parks and the solar industry in the UK are on a growth path to help the UK meet its green targets.

The Birth of The IC

Around this time 62 years ago (April 25th, 1961), Robert Noyce (co-founder of Fairchild Semiconductor) patented his invention – a monolithic integrated circuit (IC).

Jack Kilby patented a similar invention, but his version was difficult to mass produce due to external gold wire connections. Thus, Noyce’s version of the IC became widely adopted due to being more practical.

This was the first step in making computers more affordable as the new ICs reduced production costs significantly, increased efficiency and allowed for production of more powerful machines. To this day, modern chips are based on the ICs developed by Noyce.

The concept of combining multiple components in one electrical device was not new at the time. Interestingly, one of the first attempts to do so was a vacuum tube from the 1920s. It was designed for the purpose of tax avoidance in Germany, as radio receivers were taxed based on how many tube holders the receiver had.

Noyce would go on to co-found Intel. He was nicknamed the ‘Mayor of Silicon Valley’ as one of the first scientists to work there. And, because both Fairchild Semiconductor and Intel had great impact on the silicon industry.

Under Noyce’s leadership, yet another breakthrough took place at Intel. The creation of the microprocessor. He believed in a management style that promoted teamwork and sharing of ideas and was not afraid to take calculated risks. This paid off greatly, when in 1969, Marcian Hoff (a recent hire) approached him with concerns about a new design for Busicom’s electronic calculator.

That year, Intel was approached by Busicom to create a new design for their calculator. Hoff was concerned that the current design would make meeting price goals impossible. Instead, they should combine the chips to reduce complexity and costs. Which resulted in the Intel 4004, the first commercial microprocessor.

Intel went on to become a key player in the computer industry. Around 80% of personal computers in the world run on an Intel processor, meaning you are probably reading this article on a device with one and currently, Intel is valued at a whopping $128.72 billion.

Robert Noyce has left a gargantuan mark on the IT industry and the world.

If you’ve produced some content using ChatGPT and, knowing that it can sometimes generate incorrect information, would quickly like to check that the source data is from reputable sites, here’s how:

– In the window below the last response in a chat, simply type “please provide sources for the information you presented in this response” (or similar).

– ChatGPT will list the sources/links of the web pages it visited to get the information.

– If you’d like more links on the same subject, input an instruction like “list some popular links related to (subject matter here…).”

One recent example of how ChatGPT may be the subject of a defamation lawsuit after it reportedly created completely incorrect (and highly damaging) content is in the case of Brian Hood, the mayor of Hepburn Shire, 120km northwest of Melbourne, Australia. Mr Hood reported being told by members of the public that ChatGPT had (falsely) named him as a guilty party in a foreign bribery scandal involving a subsidiary of the Reserve Bank of Australia in the early 2000s. In reality, Mr Hood had been the whistleblower in the scandal, hadn’t been convicted in a crime, and hadn’t served time in prison as claimed in ChatGTP’s output about the scandal.

Even though ChatGPT can produce some convincing looking outputs, as shown in this case, it is still capable making things up or getting things wrong, so here are some ways to check the facts quickly for yourself.

How Can ChatGPT Get Things Wrong? 

As an AI language model, ChatGPT uses algorithms to generate responses based on patterns and associations learned from substantial amounts of data. ChatGPT is a machine learning AI language model and not a human being, so it may not always provide perfect responses. As OpenAI says: “Current deep learning models are not perfect. They are trained with a gigantic amount of data created by humans (e.g. on the Internet, curated and literature) and unavoidably absorb a lot of flaws and biases that long exist in our society.”

How ChatGPT Could Get Things Wrong 

Clearly, it’s possible for ChatGPT to give out incorrect/inaccurate information and even OpenAI’s boss Sam Altman has said in interviews that he thinks regulators and society should be involved with the new generative chatbot technology to guard against potentially negative consequences. Some of the main ways that ChatGPT can get things wrong include:

– Limited knowledge.  ChatGPT’s knowledge is based on the data it was trained on, which has a cut-off date of September 2021. If there is new information or developments that have occurred after that time, ChatGPT may not be aware of them. This situation may, however, soon improve when ChatGPT uses plugins, such as a web browsing plugin, to bring its answers up to date.

– It is also possible that, since ChatGPT relies on the context of the conversation to generate appropriate responses, if the context is unclear or ambiguous, ChatGPT may generate a response that is irrelevant or incorrect.

– The data that ChatGPT was trained on may contain biases that can affect the responses it generates. For example, if the training data contains a disproportionate amount of biased information on a particular topic, ChatGPT may generate responses that are biased towards that topic. Critics have also noted gender biases and other biases may be present which could skew answers.

Can’t Verify The Accuracy Of Its Answers 

It’s important to note also that ChatGPT does not have the ability to verify the accuracy of the information it provides. Therefore, as ChatGPT says itself, it’s always a good idea to fact-check any information received from ChatGPT with other sources to ensure its accuracy.

What Are The Best Ways To Fact Check?

To ensure that any ChatGPT outputs that you use are accurate, there are several ways to fact-check information, including:

– Cross-checking with other reputable source such as news articles or academic publications. If the information matches up across multiple sources, it is more likely to be accurate.

– Looking for supporting evidence such as statistics or quotes from experts. This can help you verify the accuracy of the information provided.

– Checking the credibility of the source for the information it provides, e.g. looking for information about the author, the publisher and the publication date to ensure the source is reputable and up to date.

– Using fact-checking websites such as Fullfact.org, Snopes, or FactCheck.org to verify the accuracy of information. These websites specialise in investigating and verifying information to ensure that it is accurate.

– Consulting with experts in the relevant field (if you’re able to). If you are still unsure about the accuracy of the information provided by ChatGPT, consider consulting with experts.

What Does This Mean For Your Business? 

ChatGPT is certainly a time-saving tool but is also just a machine learning AI language algorithm, albeit an impressive one. As such, given the incorrect data source and/or context, it can get things wrong so it’s worth spending a little time reading its outputs and carrying out some basic fact-checking before publishing its outputs on a website or blog. As in so many areas of business, building checks into processes can help reduce mistakes and retain quality and this is the same with using the output of generative chatbots. However, with the introduction of GPT-4 and the use of plugins, such as a web browsing plugin, ChatGPT may soon be able to produce answers that are more up-to-date and contain fewer mistakes.

With ChatGPT’s makers OpenAI facing a possible defamation lawsuit from an Australian mayor, we look at the legal aspects of online writing and publishing.

Defamed? 

Last November, when ChatGPT was first released for public use, Brian Hood, the mayor of Hepburn Shire, 120km northwest of Melbourne, was told by members of the public that ChatGPT had (falsely) named him as a guilty party in a foreign bribery scandal involving a subsidiary of the Reserve Bank of Australia in the early 2000s. In fact, Mr Hood had been the whistleblower in the scandal, hadn’t been convicted in a crime, and hadn’t served time in prison as claimed in ChatGTP’s output about the scandal. Mr Hood is, therefore reported to have instructed lawyers to send a letter of concern to OpenAI on giving the company 28 days to fix the errors about him or face a possible defamation lawsuit.

Can An AI Algorithm Defame Someone? 

Although this is a relatively new area, it could be argued that because ChatGPT is an AI language model and does not have the intent or awareness to defame someone, it may not be as clear a case as it sounds. Defamation requires a statement that is false, communicated to a third party, and causes harm to the reputation of an individual. Since ChatGPT does not have the ability to communicate with a third party outside of the conversation, it is unlikely that its responses could cause harm to an individual’s reputation in a way that would meet the legal standard for defamation.

Could The Third-Party Source Be Liable? 

However, if the information provided by ChatGPT is based on false or defamatory information from a third-party source that is repeated by ChatGPT, that third party may potentially be liable for defamation. In this case, the individual who is harmed by the false information may (as in the case of Mr Hood) be able to pursue legal action against the original source of the information.

It’s important to remember that the legal standards for defamation can vary depending on the jurisdiction, and it is always advisable to consult with a legal expert for guidance on specific cases.

What Are The Main UK Laws Relating to Online Publishing? 

Publishing online information about people is, of course, covered by laws and for publishers of content of all kinds, plus it’s worth being aware that these exist and should be adhered to. For example, in the UK, there are several laws and regulations that relate to online publishing. The main ones are:

– The Defamation Act 2013. This law sets out the rules for defamation, which occurs when a false statement is made that harms someone’s reputation. It applies to online publishing, including social media and websites.

– The Electronic Commerce (EC Directive) Regulations 2002. This regulation requires website owners to provide certain information to users, such as the website owner’s name and address, and details about any professional body or trade association they belong to.

– The Copyright, Designs and Patents Act 1988. This law protects original works such as text, images, videos, and music from being copied or used without permission. It applies to online publishing as well as offline publishing.

– The Computer Misuse Act 1990. This law makes it a criminal offense to access or modify computer systems without authorisation. This applies to online publishing, including hacking and malware attacks.

– General Data Protection Regulation (GDPR). This EU regulation, which was adopted in the UK (and made into the UK’s own version following Brexit), sets out rules for the collection, use, and storage of personal data. It applies to online publishing, including websites and social media.

– The Obscene Publications Act 1959. This law makes it an offense to publish material that is obscene, or that is likely to be harmful to the general public. This applies to online publishing, including websites and social media.

What Does This Mean For Your Business?

Although there has always been a culture of sharing and a degree of free speech on the web, uploading content to a website or platform that’s publicly available should still be regarded as publishing and, therefore, subject to many different publishing laws. In the case of ChatGPT, it’s an algorithm that has been trained on content gathered from third-party sources online and, therefore has no ‘intent’ to defame anyone, even though it has now become a popular and trusted source of information itself.

In the case of Mr Hood, it could be argued that being a public figure such as a mayor, his public reputation is of particular significance and that the third-party sources that ChatGTP’s system got the information from, and the apparent inability of ChatGPT to check the accuracy of what it produces may be central points in the case, should it go to court. When businesses use ChatGPT to produce content that they intend to publish online it is therefore worth conducting some basic fact checks, particularly where specific people and organisations are named. ChatGPT’s existence, however, shouldn’t change the fact that businesses should always be aware that there are many laws to adhere to when publishing online and that compliance is always an important issue.

With deepfake images recently making the news by fooling many people, we look at the issues around fake images and how to spot them.

Recent Examples 

The emergence of AI has led to an increasing output of highly convincing fake images/manipulated images/deepfake images (and deepfake videos). Motivations for making these images vary, e.g. entertainment (fun or visual effects in movies and TV), political propaganda, revenge, or harassment (to harass, embarrass, or intimidate individuals), to commit fraud, or simply for artistic expression.

Recent examples of fake images that have made the news include:

– Fake images of Pope Francis wearing what appears to be a $3,500 Balenciaga puffer coat.

– Fake images, circulated on social media, of former US President Donald Trump being arrested, and an AI-generated image on his own ‘Truth’ social media platform of him kneeling in prayer.

What Problems Can Fake Images Cause? 

Fake images/manipulated images/deepfake images can cause various problems depending on the context in which they are used. For example:

– Misinformation. Fake images can be used to spread false information, mislead people and create a false narrative. For example, doctored images of political events, protests, or disasters can create a misleading impression of what actually happened, potentially influencing public opinion or policy decisions.

– Reputational damage. Fake images can be used to damage the reputation of individuals or organisations. For example, a fake image of a celebrity engaging in illegal or immoral activity can cause significant harm to their public image.

– Legal issues. Fake images can be used as evidence in legal cases, but if they are not authentic, they can lead to wrongful convictions or acquittals. Moreover, fake images can cause copyright and intellectual property issues.

– Security threats. Fake images can be used to create security threats. For example, a fake image of a terrorist attack or a natural disaster can cause panic and chaos among people, leading to a security breach.

– Personal harm. Fake images can be used to harass, intimidate, or blackmail individuals. For example, a fake image of a person engaging in illegal or embarrassing activity can be used to blackmail or extort money from them. This gained notoriety with the trend of fake-pornographic images of well known celebrities, causing significant distress.

It should also be noted that some fake images can simply be a source of amusement or wonder over how AI has advanced and could be be seen as an example of how difficult it can now be to tell the difference between a real and a fake photo.

How Are Fake Photos Made? 

Examples of the kinds of tools now used to make fake photos include:

– More traditional photo editing software like Adobe Photoshop, e.g. using the Clone Stamp tool to duplicate elements of an image and cover up unwanted objects, or the Liquify tool to reshape and distort a person’s features.

– Online image editing tools: Several online image editing tools, such as Fotor, PicMonkey, and BeFunky, provide basic image editing capabilities that can be used to create fake photos, such as adding text, filters, and borders to an image.

Deepfake software, such as DeepFaceLab, FakeApp, and Zao, use machine learning algorithms to create realistic fake photos and videos by swapping faces or manipulating the appearance of a person.

– GANs (Generative Adversarial Networks), a type of artificial intelligence that can be used to generate realistic images. GANs consist of two neural networks, a generator that creates images and a discriminator that tries to distinguish real images from fake ones. As the generator learns, it can create more realistic images, making it a powerful tool for creating fake photos.

There are now many different AI programs that can be used to create fake images such as Generated.photos, This Person Does Not Exist: Random Face Generator, Shutterstock Generate, Jasper, Picsart, and even the next generation of ChatGPT, some of which can now instantly generate photos from a text description.

How To Spot A Fake Image 

With so many fake images around and so many AI-powered programs available, how can you spot a fake image?  Here are some common giveaways:

– Unnatural or inconsistent lighting. If the lighting in the image looks unnatural or inconsistent, such as different parts of the image having different shadows or light sources, it could be a sign that the image has been manipulated.

– Pixelation or blurring. If parts of the image look pixelated or blurred, it could be a sign that they have been altered. This is because when an image is edited, it often loses some of its original quality.

– Perspective and proportions. If the proportions or perspective in the image look distorted or inconsistent, it could be a sign that the image has been manipulated. For example, if a person’s head looks too big or too small for their body or if an object looks like it’s floating in the air, it could be a sign that it has been added to the image. It is often noted that hands can be a difficult area for fake image programs to get right, and the direction of eyes in a photo where there are multiple persons can also be a giveaway.

– Inconsistencies in shadows. If there are inconsistencies in the shadows in the image, it could be a sign that the image has been manipulated. For example, if a person’s shadow falls in a different direction than the other objects in the scene, it could indicate that the person has been added to the image.

– Lack of context. If the image lacks context or appears to be taken out of its original context, it could be a sign that it has been manipulated. For example, if an image shows a person in front of a particular background, but the person does not appear to be interacting with their surroundings, it could indicate that the person has been added to the image.

– Although it’s important to be vigilant and critical when viewing images online and to look for signs of manipulation, it’s also a good idea, if in doubt, to know how to and to try to verify the authenticity of an image by checking the original source.

Verifying Images

Verifying the authenticity of an image can be challenging, however there are several steps you can take to help determine if an image is real or has been manipulated:

– Check the source. One of the easiest ways to verify the authenticity of an image is to check its source. If the image is from a reputable news outlet, a government agency, or a trustworthy website, it is more likely to be real. However, if the image is from an unknown source or an unverified social media account, it could be fake.

– Look for metadata. Metadata is information embedded in the image file that can provide details about when and where the image was taken, the camera used, and other relevant information. You can use image analysis software or online tools to view the metadata of an image and determine if it matches the content of the image.

– Use a reverse image search. A reverse image search can help you find out where an image has been used before and whether it has been altered. You can use search engines such as Google Images or TinEye to upload the image or its URL and see if there are any matches.

– In more high-profile cases that make the news, there is also the option of consulting with experts in image analysis or forensics who can examine the image and provide a professional opinion. This can be especially helpful in cases where the image is of significant importance or is being used to influence public opinion.

Overall, verifying the authenticity of an image requires critical thinking, attention to detail and a willingness to do some research. By following these steps, you can increase your chances of determining if an image is real or fake.

What Does This Mean For Your Business? 

The pace at which AI is advancing has meant that much more convincing fake images (and videos) can be made more quickly and easily and it’s this pace that’s recently alarmed some people into calling for a 6 month pause on the development of AI systems to assess the risks (a 1,800 signature open-letter, including Elon Musk’s). Although there are many ways to spot and verify fake photos, it looks likely that this is going to become more difficult to check and we even need the help of AI to help us spot AI generated deepfakes. Even the powerful social media platforms haven’t been able to stop fake profile photos and the circulation of fake photos and videos on their platforms are cause for concern, e.g. spreading propaganda/misinformation and is something the social media platforms will need to get a firmer grip on. It could be argued that education and awareness of news and world events is one important way that people can be aware of context and be better able to develop a healthy scepticism and be more able to spot fake photos and their possible motivations. For businesses, being able to identify fake photos is an important issue from a security and legal perspective so it’s important to be familiar with popular ways to tell the difference between real and fake photos and how to verify photo (and video) authenticity.

Changes to Microsoft 365 could mean less OneDrive cloud storage and could lead to Outlook being disrupted.

Change 

In February, Microsoft announced that cloud storage used across Microsoft 365 apps and services would include Outlook.com attachments data and OneDrive data. Microsoft has warned that this change could reduce how much cloud storage users have available to use with their OneDrive and, if the cloud storage quota is reached, the ability of users to send and receive emails in Outlook.com will be disrupted.

What’s Included In Microsoft cloud storage? 

A user’s Microsoft storage quota applies to a personal Microsoft account and includes OneDrive files and photos, e.g. personal files uploaded and synchronised from a computer or mobile device, such as Office documents, photos and other files saved to OneDrive, and items in the recycle bin. It also includes Outlook.com attachments and email in-line images, Microsoft Teams message attachments and recordings.

What Does This Mean? 

Whereas users used to be allowed to have a maximum of 15GB of storage in their cloud-hosted email which included text and attachments, and 5GB in their OneDrive storage, attachments now count as part of the 5GB OneDrive allowance. This is not just a significant reduction of storage space available as part of the account but also means the threat of disruption to services if/when the smaller storage quota is reached. Also, the change means that unless users keep deleting emails with attachments (which few people are likely to do) that could push them over the new limit.

Not Aware 

Another problem may be that many users may simply not be aware of the recent policy change and could face disruption without knowing why.

There have also been reports of users who were unaware that the attachments shifting over to OneDrive were the cause of their email problems and deleted a lot of emails in response, only to discover that this didn’t change the “storage used” amount.

Gradual Rollout 

The fact that Microsoft says that the new storage change is to have a gradual rollout also puts the responsibility onto users to keep checking their Windows settings, and Microsoft account to see if they are likely to experience some storage problems.

Subscription  

Some commentators have suggested that the policy change could lead some users to think that it’s a move by Microsoft to make users buy a subscription by the back door.

What Does This Mean For Your Business? 

For users who’ve had a Microsoft account for some time, this change may not only take them by surprise and potentially cause some confusion and disruption but may also leave them feeling annoyed that they’re being pushed towards either buying a subscription to get 50GB of email storage or facing the extra work of having to keep deleting emails with attachments. If users are already invested with their Microsoft account, the barrier to switching may seem high, however some online commentators have pointed out that Google’s Gmail accounts come with a 15GB limit which may have seemed an attractive alternative.