#FactCheck - False Claim of Italian PM Congratulating on Ram Temple, Reveals Birthday Thanks

Introduction

According to Statista, the global artificial intelligence software market is forecast to grow by around 126 billion US dollars by 2025. This will include a 270% increase in enterprise adoption over the past four years. The top three verticals in the Al market are BFSI (Banking, Financial Services, and Insurance), Healthcare & Life Sciences, and Retail & e-commerce. These sectors benefit from vast data generation and the critical need for advanced analytics. Al is used for fraud detection, customer service, and risk management in BFSI; diagnostics and personalised treatment plans in healthcare; and retail marketing and inventory management.

The Chairperson of the Competition Commission of India’s Chief, Smt. Ravneet Kaur raised a concern that Artificial Intelligence has the potential to aid cartelisation by automating collusive behaviour through predictive algorithms. She explained that the mere use of algorithms cannot be anti-competitive but in case the algorithms are manipulated, then that is a valid concern about competition in markets.

This blog focuses on how policymakers can balance fostering innovation and ensuring fair competition in an AI-driven economy. 

What is the Risk Created by AI-driven Collusion?

AI uses predictive algorithms, and therefore, they could lead to aiding cartelisation by automating collusive behaviour. AI-driven collusion could be through:

• The use of predictive analytics to coordinate pricing strategies among competitors.
• The lack of human oversight in algorithm-induced decision-making leads to tacit collusion (competitors coordinate their actions without explicitly communicating or agreeing to do so).

AI has been raising antitrust concerns and the most recent example is the partnership between Microsoft and OpenAI, which has raised concerns among other national competition authorities regarding potential competition law issues. While it is expected that the partnership will potentially accelerate innovation, it also raises concerns about potential anticompetitive effects such as market foreclosure or the creation of barriers to entry for competitors and, therefore, has been under consideration in the German and UK courts. The problem here is in detecting and proving whether collusion is taking place. 

The Role of Policy and Regulation

The uncertainties induced by AI regarding its effects on competition create the need for algorithmic transparency and accountability in mitigating the risks of AI-driven collusion. It leads to the need to build and create regulatory frameworks that mandate the disclosure of algorithmic methodologies and establish a set of clear guidelines for the development of AI and its deployment. These frameworks or guidelines should encourage an environment of collaboration between competition watchdogs and AI experts. 

The global best practices and emerging trends in AI regulation already include respect for human rights, sustainability, transparency and strong risk management. The EU AI Act could serve as a model for other jurisdictions, as it outlines measures to ensure accountability and mitigate risks. The key goal is to tailor AI regulations to address perceived risks while incorporating core values such as privacy, non-discrimination, transparency, and security.

Promoting Innovation Without Stifling Competition

Policymakers need to ensure that they balance regulatory measures with innovation scope and that the two priorities do not hinder each other. 

1. Create adaptive and forward-thinking regulatory approaches to keep pace with technological advancements that take place at the pace of development and allow for quick adjustments in response to new AI capabilities and market behaviours.n
2. Competition watchdogs need to recruit domain experts to assess competition amid rapid changes in the technology landscape. Create a multi-stakeholder approach that involves regulators, industry leaders, technologists and academia who can create inclusive and ethical AI policies. 
3. Businesses can be provided incentives such as recognition through certifications, grants or benefits in acknowledgement of adopting ethical AI practices. 
4. Launch studies such as the CCI’s market study to study the impact of AI on competition. This can lead to the creation of a driving force for sustainable growth with technological advancements. 

Conclusion: AI and the Future of Competition

We must promote a multi-stakeholder approach that enhances regulatory oversight, and incentivising ethical AI practices. This is needed to strike a delicate balance that safeguards competition and drives sustainable growth. As AI continues to redefine industries, embracing collaborative, inclusive, and forward-thinking policies will be critical to building an equitable and innovative digital future. 

The lawmakers and policymakers engaged in the drafting of the frameworks need to ensure that they are adaptive to change and foster innovation. It is necessary to note that fair competition and innovation are not mutually exclusive goals, they are complementary to each other. Therefore, a regulatory framework that promotes transparency, accountability, and fairness in AI deployment must be established.

References

• https://www.thehindu.com/sci-tech/technology/ai-has-potential-to-aid-cartelisation-fair-competition-integral-for-sustainable-growth-cci-chief/article69041922.ece 
• https://www.marketsandmarkets.com/Market-Reports/artificial-intelligence-market-74851580.html 
• https://www.ey.com/en_in/insights/ai/how-to-navigate-global-trends-in-artificial-intelligence-regulation#:~:text=Six%20regulatory%20trends%20in%20Artificial%20Intelligence&text=These%20include%20respect%20for%20human,based%20approach%20to%20AI%20regulation. ‍
• https://www.business-standard.com/industry/news/ai-has-potential-to-aid-fair-competition-for-sustainable-growth-cci-chief-124122900221_1.html

In the rich history of humanity, the advent of artificial intelligence (AI) has added a new, delicate aspect. The aspect of promising technological advancement has the potential to either enrich the nest of our society or destroy it entirely. The latest straw in this complex nest is generative AI, a frontier teeming with both potential and perils. It is a realm where the ethereal concepts of cyber peace and resilience are not just theoretical constructs but tangible necessities.

The spectre of generative AI looms large over the digital landscape, casting a long shadow on the sanctity of data privacy and the integrity of political processes. The seeds of this threat were sown in the fertile soil of the Cambridge Analytica scandal of 2018, a watershed moment that unveiled the extent to which personal data could be harvested and utilized to influence electoral outcomes. However despite the indignation, the scandal resulted in meagre alterations to modus operandi of digital platforms.

Fast forward to the present day, and the spectre has only grown more ominous. A recent report by Human Rights Watch has shed light on the continued exploitation of data-driven campaigning in Hungary's re-election of Viktor Orbán. The report paints a chilling picture of political parties leveraging voter databases for targeted social media advertising, with the ruling Fidesz party even resorting to the unethical use of public service data to bolster its voter database.

The Looming Threat of Disinformation

As we stand on the precipice of 2024, a year that will witness over 50 countries holding elections, the advancements in generative AI could exponentially amplify the ability of political campaigns to manipulate electoral outcomes. This is particularly concerning in countries where information disparities are stark, providing fertile ground for the seeds of disinformation to take root and flourish.

The media, the traditional watchdog of democracy, has already begun to sound the alarm about the potential threats posed by deepfakes and manipulative content in the upcoming elections. The limited use of generative AI in disinformation campaigns has raised concerns about the enforcement of policies against generating targeted political materials, such as those designed to sway specific demographic groups towards a particular candidate.

Yet, while the threat of bad actors using AI to generate and disseminate disinformation is real and present, there is another dimension that has largely remained unexplored: the intimate interactions with chatbots. These digital interlocutors, when armed with advanced generative AI, have the potential to manipulate individuals without any intermediaries. The more data they have about a person, the better they can tailor their manipulations.

Root of the Cause 

To fully grasp the potential risks, we must journey back 30 years to the birth of online banner ads. The success of the first-ever banner ad for AT&T, which boasted an astounding 44% click rate, birthed a new era of digital advertising. This was followed by the advent of mobile advertising in the early 2000s. Since then, companies have been engaged in a perpetual quest to harness technology for manipulation, blurring the lines between commercial and political advertising in cyberspace.

Regrettably, the safeguards currently in place are woefully inadequate to prevent the rise of manipulative chatbots. Consider the case of Snapchat's My AI generative chatbot, which ostensibly assists users with trivia questions and gift suggestions. Unbeknownst to most users, their interactions with the chatbot are algorithmically harvested for targeted advertising. While this may not seem harmful in its current form, the profit motive could drive it towards more manipulative purposes.

If companies deploying chatbots like My AI face pressure to increase profitability, they may be tempted to subtly steer conversations to extract more user information, providing more fuel for advertising and higher earnings. This kind of nudging is not clearly illegal in the U.S. or the EU, even after the AI Act comes into effect. The market size of AI in India is projected to touch US$4.11bn in 2023. 

Taking this further, chatbots may be inclined to guide users towards purchasing specific products or even influencing significant life decisions, such as religious conversions or voting choices. The legal boundaries here remain unclear, especially when manipulation is not detectable by the user. 

The Crucial Dos/Dont's 

It is crucial to set rules and safeguards in order to manage the possible threats related to manipulative chatbots in the context of the general election in 2024.

First and foremost, candor and transparency are essential. Chatbots, particularly when employed for political or electoral matters, ought to make it clear to users what they are for and why they are automated. By being transparent, people are guaranteed to be aware that they are interacting with automated processes.

Second, getting user consent is crucial. Before collecting user data for any reason, including advertising or political profiling, users should be asked for their informed consent. Giving consumers easy ways to opt-in and opt-out gives them control over their data.

Furthermore, moral use is essential. It's crucial to create an ethics code for chatbot interactions that forbids manipulation, disseminating false information, and trying to sway users' political opinions. This guarantees that chatbots follow moral guidelines.

In order to preserve transparency and accountability, independent audits need to be carried out. Users might feel more confident knowing that chatbot behavior and data collecting procedures are regularly audited by impartial third parties to ensure compliance with legal and ethical norms.

Important "don'ts" to take into account. Coercion and manipulation ought to be outlawed completely. Chatbots should refrain from using misleading or manipulative approaches to sway users' political opinions or religious convictions.

Another hazard to watch out for is unlawful data collecting. Businesses must obtain consumers' express agreement before collecting personal information, and they must not sell or share this information for political reasons.

At all costs, one should steer clear of fake identities. Impersonating people or political figures is not something chatbots should do because it can result in manipulation and false information.

It is essential to be impartial. Bots shouldn't advocate for or take part in political activities that give preference to one political party over another. In encounters, impartiality and equity are crucial.

Finally, one should refrain from using invasive advertising techniques. Chatbots should ensure that advertising tactics comply with legal norms by refraining from displaying political advertisements or messaging without explicit user agreement.

Present Scenario

As we approach the critical 2024 elections and generative AI tools proliferate faster than regulatory measures can keep pace, companies must take an active role in building user trust, transparency, and accountability. This includes comprehensive disclosure about a chatbot's programmed business goals in conversations, ensuring users are fully aware of the chatbot's intended purposes.

To address the regulatory gap, stronger laws are needed. Both the EU AI Act and analogous laws across jurisdictions should be expanded to address the potential for manipulation in various forms. This effort should be driven by public demand, as the interests of lawmakers have been influenced by intensive Big Tech lobbying campaigns.

At present, India doesn’t have any specific laws pertaining to AI regulation. Ministry of Electronics and Information Technology (MEITY), is the executive body responsible for AI strategies and is constantly working towards a policy framework for AI. The Niti Ayog has presented seven principles for responsible AI which includes equality , inclusivity, safety, privacy, transparency, accountability, dependability and protection of positive human values.

Conclusion 

We are at a pivotal juncture in history. As generative AI gains more power, we must proactively establish effective strategies to protect our privacy, rights and democracy. The public's waning confidence in Big Tech and the lessons learned from the techlash underscore the need for stronger regulations that hold tech companies accountable. Let's ensure that the power of generative AI is harnessed for the betterment of society and not exploited for manipulation.

Reference

McCallum, B. S. (2022, December 23). Meta settles Cambridge Analytica scandal case for $725m. BBC News. https://www.bbc.com/news/technology-64075067

Hungary: Data misused for political campaigns. (2022, December 1). Human Rights Watch. https://www.hrw.org/news/2022/12/01/hungary-data-misused-political-campaigns

Statista. (n.d.). Artificial Intelligence - India | Statista Market forecast. https://www.statista.com/outlook/tmo/artificial-intelligence/india

Introduction

Election misinformation poses a major threat to democratic processes all over the world. The rampant spread of misleading information intentionally (disinformation) and unintentionally (misinformation) during the election cycle can not only create grounds for voter confusion with ramifications on election results but also incite harassment, bullying, and even physical violence. The attack on the United States Capitol Building in Washington D.C., in 2021, is a classic example of this phenomenon, where the spread of dis/misinformation snowballed into riots. 

Election Dis/Misinformation 

Election dis/misinformation is false or misleading information that affects/influences public understanding of voting, candidates, and election integrity. The internet, particularly social media, is the foremost source of false information during elections. It hosts fabricated news articles, posts or messages containing incorrectly-captioned pictures and videos, fabricated websites, synthetic media and memes, and distorted truths or lies. In a recent example during the 2024 US elections, fake videos using the Federal Bureau of Investigation’s (FBI) insignia alleging voter fraud in collusion with a political party and claiming the threat of terrorist attacks were circulated. According to polling data collected by Brookings, false claims influenced how voters saw candidates and shaped opinions on major issues like the economy, immigration, and crime. It also impacted how they viewed the news media’s coverage of the candidates’ campaign. The shaping of public perceptions can thus, directly influence election outcomes. It can increase polarisation, affect the quality of democratic discourse, and cause disenfranchisement. From a broader perspective, pervasive and persistent misinformation during the electoral process also has the potential to erode public trust in democratic government institutions and destabilise social order in the long run.  

Challenges In Combating Dis/Misinformation

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1. Platform Limitations:  Current content moderation practices by social media companies struggle to identify and flag misinformation effectively. To address this, further adjustments are needed, including platform design improvements, algorithm changes, enhanced content moderation, and stronger regulations.

2. Speed and Spread: Due to increasingly powerful algorithms, the speed and scale at which misinformation can spread is unprecedented. In contrast, content moderation and fact-checking are reactive and are more time-consuming. Further, incendiary material, which is often the subject of fake news, tends to command higher emotional engagement and thus, spreads faster (virality). 

3. Geopolitical influences: Foreign actors seeking to benefit from the erosion of public trust in the USA present a challenge to the country's governance, administration and security machinery. In 2018, the federal jury indicted 11 Russian military officials for alleged computer hacking to gain access to files during the 2016 elections.  Similarly, Russian involvement in the 2024 federal elections has been alleged by high-ranking officials such as White House national security spokesman John Kirby, and Attorney General Merrick Garland. 

4. Lack of Targeted Plan to Combat Election Dis/Misinformation:  In the USA,  dis/misinformation is indirectly addressed through laws on commercial advertising, fraud, defamation, etc. At the state level, some laws such as Bills AB 730, AB 2655, AB 2839, and AB 2355 in California target election dis/misinformation. The federal and state governments criminalize false claims about election procedures, but the Constitution mandates  “breathing space” for protection from false statements within election speech. This makes it difficult for the government to regulate election-related falsities.

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CyberPeace Recommendations

1. Strengthening Election Cybersecurity Infrastructure: To build public trust in the electoral process and its institutions, security measures such as updated data protection protocols, publicized audits of election results, encryption of voter data, etc. can be taken. In 2022, the federal legislative body of the USA  passed the Electoral Count Reform and Presidential Transition Improvement Act (ECRA), pushing reforms allowing only a state’s governor or designated executive official to submit official election results, preventing state legislatures from altering elector appointment rules after Election Day and making it more difficult for federal legislators to overturn election results. More investments can be made in training, scenario planning, and fact-checking for more robust mitigation of election-related malpractices online. 
2. Regulating Transparency on Social Media Platforms: Measures such as transparent labeling of election-related content and clear disclosure of political advertising to increase accountability can make it easier for voters to identify potential misinformation. This type of transparency is a necessary first step in the regulation of content on social media and is useful in providing disclosures, public reporting, and access to data for researchers. Regulatory support is also required in cases where popular platforms actively promote election misinformation.
3. Increasing focus on ‘Prebunking’ and Debunking Information: Rather than addressing misinformation after it spreads, ‘prebunking’ should serve as the primary defence to strengthen public resilience ahead of time. On the other hand, misinformation needs to be debunked repeatedly through trusted channels. Psychological inoculation techniques against dis/misinformation can be scaled to reach millions on social media through short videos or messages.
4. Focused Interventions On Contentious Themes By Social Media Platforms: As platforms prioritize user growth, the burden of verifying the accuracy of posts largely rests with users. To shoulder the responsibility of tackling false information, social media platforms can outline critical themes with large-scale impact such as anti-vax content, and either censor, ban, or tweak the recommendations algorithm to reduce exposure and weaken online echo chambers. 
5. Addressing Dis/Information through a Socio-Psychological Lens: Dis/misinformation and its impact on domains like health, education, economy, politics, etc. need to be understood through a psychological and sociological lens, apart from the technological one. A holistic understanding of the propagation of false information should inform digital literacy training in schools and public awareness campaigns to empower citizens to evaluate online information critically. 

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Conclusion

According to the World Economic Forum’s Global Risks Report 2024, the link between misleading or false information and societal unrest will be a focal point during elections in several major economies over the next two years. Democracies must employ a mixed approach of immediate tactical solutions, such as large-scale fact-checking and content labelling, and long-term evidence-backed countermeasures, such as digital literacy, to curb the spread and impact of dis/misinformation.

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Sources

•  https://www.cbsnews.com/news/2024-election-misinformation-fbi-fake-videos/ 
•  https://www.brookings.edu/articles/how-disinformation-defined-the-2024-election-narrative/ 
•  https://www.fbi.gov/wanted/cyber/russian-interference-in-2016-u-s-elections
• https://indianexpress.com/article/world/misinformation-spreads-fear-distrust-ahead-us-election-9652111/ 
•  https://academic.oup.com/ajcl/article/70/Supplement_1/i278/6597032#377629256 
• https://www.brennancenter.org/our-work/policy-solutions/how-states-can-prevent-election-subversion-2024-and-beyond 
•  https://www.bbc.com/news/articles/cx2dpj485nno 
• https://msutoday.msu.edu/news/2022/how-misinformation-and-disinformation-influence-elections 
• https://misinforeview.hks.harvard.edu/article/a-survey-of-expert-views-on-misinformation-definitions-determinants-solutions-and-future-of-the-field/ 
• https://reutersinstitute.politics.ox.ac.uk/sites/default/files/2023-06/Digital_News_Report_2023.pdf 
• https://www.weforum.org/stories/2024/03/disinformation-trust-ecosystem-experts-curb-it/ 
• https://www.apa.org/topics/journalism-facts/misinformation-recommendations 
• https://mythvsreality.eci.gov.in/ 
• https://www.brookings.edu/articles/transparency-is-essential-for-effective-social-media-regulation/ 
• https://www.brookings.edu/articles/how-should-social-media-platforms-combat-misinformation-and-hate-speech/ 

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