Digital Innovations and Smart Solutions for Society and Economy: Pros and Cons

– Undermining public order and trust to state, businesses, and society

– Affecting AI-based governments, justice, etc.

– Generating false recommendations, judgments, and decisions

– State abusing the use of automated electronic surveillance

– Automated AI-based censorship online

– Social manipulation for rebel or pro-government campaigns

– Social trust put on fabricated entities interacting online like humans

– Malicious hijacking online campaigns

– Impersonalized, anonymous, distant relation to state or institutions

– IT-initiated crashes and disruptions (caused or accidental)

– Generating false alarms and panic

– Remote or delayed attack operations

– Robots disabling or entering security zones and damaging infrastructures

– Machine-based false judgments and decisions leading to material loss

– Human sabotage and damage of automated surveillance equipment

– Disruption of markets or regional economies

– Paralyzing important institutions

– Manipulations in social media for discrediting business brands

– Business-oriented manipulations aimed at affecting conjuncture

– Reputational damages, erosion of trust

– Financial losses and damages due to malicious activities online

– Criminal, legal, or insurance problems

– AI used for streamlining users from/to specific content

– AI-propelled emotional scam (dating, financial, etc.)

– Privacy violations, data breach

– AI-based medical misdiagnosis, physical/health damages

– AI-based abusive profiling of users, patients, or consumers

– Undermined personal trust to state, businesses, and society

– Self-imposed auto-censorship due to ubiquitous online surveillance

– Fabricated evidences (videos) in media or in judicial cases

– Personal addiction to digital platforms (social, entertainment, etc.)

– Using AI to accessing classified information

– Using AI to attack critical infrastructure, command centers

– Overtaking control, mimicking human operators

– Creating a panic, provoking conflicts affecting national security

– AI-controlled robots disabling national security

– Allowing AI to use incorrect or incomplete input data

– Technological flaws resulting in suboptimal decisions or control actions

– Poor quality of AI: faulty machine learning, inadequate supervision

– Attacks self-initiated by AI, self-initiated modification of software

– Lack of explainability, transparency, and traceability of AI software

– Learning and adaptation of AI software is beyond human control

– Dual use of AI software: for terrorism, hijacking, overtaking control

– Automated fabricating of data, news for blackmailing or discrediting

– Swamping information channels with noise

– AI-based prioritizing of attack targets, automated vulnerability discovery

– Open code, open algorithms, destructive tools easier to develop

– Human reprogramming AI for malicious use

– Corrupting algorithms by disgusted employees or external foes

– Hijacking autonomous vehicles or software robots (overtaking control)

– Building and deploying malicious bots or robots

– Nanobots for deploying toxins to the environment or living bodies

– Fake news for destabilizing, manipulating elections

– Automated social engineering attacks

– Malicious chatbots mimicking humans, chatbots pretending as friends

– Automated influence campaigning (elections, shopping, etc.)

– Automated scam and targeted blackmail

– Social bots propagating or draw-in to extreme/hysteric groups

– Malicious streamlining of users to/from a specific content

– Greed, rush, releasing untested, unvalidated software

– Ignorance or recklessness of business leaders or companies

– No governance, no supervision, no ethics related to AI

– No AI-related risk management activities

– No recovery plans for AI-related damages/impacts

– No forecasting/assessment of social effects caused by AI

– No dedicated consumer protection from AI (smart) products

– No control/registry of AI software applications

– Lack of coordinated supervision or one responsible body on a national level

– Leaders unaware of or ignoring the opinions of experts

– Poor awareness of customers with regard to AI-caused harms

– No systematic risk analysis, no forecasting, no foresights

– No lessons learned from reported incidents

– No risk identification performed as to the social impact of AI

– AI-related gaps in the legal system, lacking standards and procedures

– Monitoring systems and behaviors, early detection of hackers

– Adapting cybersecurity techniques to smart systems

– Compromising attackers (buy-in)

– AI tools used reversely – for security and defense

– “Red-teams” forecasting malicious activities for security, fraud, or abuse

– Educating consumers about threats from “smart” products

– Expert bodies to be heard louder than now

– Publishing case studies on incidents and threats affecting real life

– Presenting AI with a balanced view, objective tone, and no hype

– Expert bodies answering questions from consumers

– Promoting consumer rights to have smart systems safe and validated

– Educating consumers in critical thinking as to biased or fake news

– Providing free tools for validating credibility of news and media sources

– Promoting ethical AI to engineers and prospective developers (students)

– Interdisciplinary design teams able to assess social impact

– Including new (public and social) stakeholders into design process

– Feeding from social sciences, not only from tech domains

– Promoting mandatory assessment of the social impact of AI applications

– Rewarding ethical and sustainable governance in AI business companies

– Implementing supervised design, deployment and operation of AI

– Assuring AI compliance to regulations (auditing, certificates)

– Assigning process owners and leadership in AI business governance

– Company monitoring assessments of the social impact of AI

– Promoting explainability and traceability of AI algorithms

– Improving the regulatory framework for technological solutions

– Establishing a repository of AI-related incidents and damages

– Assigning one major AI-regulatory institution on the national level

– Formalizing communication: regulators, governments, and AI business

– Legal requirements for auditing, certification, and verification of AI

– Intelligence involved in monitoring AI-related incidents and damages

– Protecting AI against unauthorized reverse engineering and decoding

– Hardware supply chain control: hardware manufacturers and distributors

– Software supply chain control for critical AI components

– Mandatory registration and insurance for robots/drones/vehicles

– Regulatory institutions make pressure on governments to update the law

– Standardized security barriers to airspace and other open spaces

– Assigning one major AI regulatory institution on the national level

– Automated detections and automated interventions

– Surveillance of and moderating social media, public health discourse

– Banning specific AI technologies from authoritarian governments

– Pervasive use of total encryption

– Technical tools for detecting malicious bots, fake news, and forgeries